{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Implementing a Neural Network\n",
    "In this exercise we will develop a neural network with fully-connected layers to perform classification, and test it out on the CIFAR-10 dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A bit of setup\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from cs231n.classifiers.neural_net import TwoLayerNet\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# for auto-reloading external modules\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "def rel_error(x, y):\n",
    "  \"\"\" returns relative error \"\"\"\n",
    "  return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the class `TwoLayerNet` in the file `cs231n/classifiers/neural_net.py` to represent instances of our network. The network parameters are stored in the instance variable `self.params` where keys are string parameter names and values are numpy arrays. Below, we initialize toy data and a toy model that we will use to develop your implementation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a small net and some toy data to check your implementations.\n",
    "# Note that we set the random seed for repeatable experiments.\n",
    "\n",
    "input_size = 4\n",
    "hidden_size = 10\n",
    "num_classes = 3\n",
    "num_inputs = 5\n",
    "\n",
    "def init_toy_model():\n",
    "  np.random.seed(0)\n",
    "  return TwoLayerNet(input_size, hidden_size, num_classes, std=1e-1)\n",
    "\n",
    "def init_toy_data():\n",
    "  np.random.seed(1)\n",
    "  X = 10 * np.random.randn(num_inputs, input_size)\n",
    "  y = np.array([0, 1, 2, 2, 1])\n",
    "  return X, y\n",
    "\n",
    "net = init_toy_model()\n",
    "X, y = init_toy_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forward pass: compute scores\n",
    "Open the file `cs231n/classifiers/neural_net.py` and look at the method `TwoLayerNet.loss`. This function is very similar to the loss functions you have written for the SVM and Softmax exercises: It takes the data and weights and computes the class scores, the loss, and the gradients on the parameters. \n",
    "\n",
    "Implement the first part of the forward pass which uses the weights and biases to compute the scores for all inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your scores:\n",
      "[[-0.81233741 -1.27654624 -0.70335995]\n",
      " [-0.17129677 -1.18803311 -0.47310444]\n",
      " [-0.51590475 -1.01354314 -0.8504215 ]\n",
      " [-0.15419291 -0.48629638 -0.52901952]\n",
      " [-0.00618733 -0.12435261 -0.15226949]]\n",
      "correct scores:\n",
      "[[-0.81233741 -1.27654624 -0.70335995]\n",
      " [-0.17129677 -1.18803311 -0.47310444]\n",
      " [-0.51590475 -1.01354314 -0.8504215 ]\n",
      " [-0.15419291 -0.48629638 -0.52901952]\n",
      " [-0.00618733 -0.12435261 -0.15226949]]\n",
      "Difference between your scores and correct scores:\n",
      "3.6802720496109664e-08\n"
     ]
    }
   ],
   "source": [
    "scores = net.loss(X)\n",
    "print ('Your scores:')\n",
    "print (scores)\n",
    "print\n",
    "print ('correct scores:')\n",
    "correct_scores = np.asarray([\n",
    "  [-0.81233741, -1.27654624, -0.70335995],\n",
    "  [-0.17129677, -1.18803311, -0.47310444],\n",
    "  [-0.51590475, -1.01354314, -0.8504215 ],\n",
    "  [-0.15419291, -0.48629638, -0.52901952],\n",
    "  [-0.00618733, -0.12435261, -0.15226949]])\n",
    "print (correct_scores)\n",
    "print\n",
    "\n",
    "# The difference should be very small. We get < 1e-7\n",
    "print ('Difference between your scores and correct scores:')\n",
    "print (np.sum(np.abs(scores - correct_scores)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Forward pass: compute loss\n",
    "In the same function, implement the second part that computes the data and regularizaion loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Difference between your loss and correct loss:\n",
      "1.7985612998927536e-13\n"
     ]
    }
   ],
   "source": [
    "loss, _ = net.loss(X, y, reg=0.1)\n",
    "correct_loss = 1.30378789133\n",
    "\n",
    "# should be very small, we get < 1e-12\n",
    "print ('Difference between your loss and correct loss:')\n",
    "print (np.sum(np.abs(loss - correct_loss)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Backward pass\n",
    "Implement the rest of the function. This will compute the gradient of the loss with respect to the variables `W1`, `b1`, `W2`, and `b2`. Now that you (hopefully!) have a correctly implemented forward pass, you can debug your backward pass using a numeric gradient check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "W2 max relative error: 3.440708e-09\n",
      "b2 max relative error: 3.865091e-11\n",
      "W1 max relative error: 3.561318e-09\n",
      "b1 max relative error: 1.555470e-09\n"
     ]
    }
   ],
   "source": [
    "from cs231n.gradient_check import eval_numerical_gradient\n",
    "\n",
    "# Use numeric gradient checking to check your implementation of the backward pass.\n",
    "# If your implementation is correct, the difference between the numeric and\n",
    "# analytic gradients should be less than 1e-8 for each of W1, W2, b1, and b2.\n",
    "\n",
    "loss, grads = net.loss(X, y, reg=0.1)\n",
    "\n",
    "# these should all be less than 1e-8 or so\n",
    "for param_name in grads:\n",
    "  f = lambda W: net.loss(X, y, reg=0.1)[0]\n",
    "  param_grad_num = eval_numerical_gradient(f, net.params[param_name], verbose=False)\n",
    "  print ('%s max relative error: %e' % (param_name, rel_error(param_grad_num, grads[param_name])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train the network\n",
    "To train the network we will use stochastic gradient descent (SGD), similar to the SVM and Softmax classifiers. Look at the function `TwoLayerNet.train` and fill in the missing sections to implement the training procedure. This should be very similar to the training procedure you used for the SVM and Softmax classifiers. You will also have to implement `TwoLayerNet.predict`, as the training process periodically performs prediction to keep track of accuracy over time while the network trains.\n",
    "\n",
    "Once you have implemented the method, run the code below to train a two-layer network on toy data. You should achieve a training loss less than 0.2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final training loss:  1.2514407670819387\n"
     ]
    },
    {
     "data": {
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uGznnL+acv/jEiRM1Hylx1LlyIIOzNrZ6xtyVs1Gfs2D4OSlnufSDmrO9gdN4Y0mCIOaLVM7G0pqknKXDGHs6Y8KwgDH2LwAYAK4D+DiAZzDG7mKMGQC+FcBfLeo4iZuL7X1hQHtqrY3NnjGxIeDRywd41/2XKnv9UZ8zqZxRcJaHTGvanh+qaARBEMB4cCaVs6bXnGl1PTFj7C0AvhzAccbYeQCvA6ADAOf8vwH4JgDfyRhzAAwBfEvQIOAyxn4QwN8BUAH8Luf8wbqOkyDiyLTmidUWNrv6RHuGN37gc3jvI9v42ufeUsnrC5+zyEoDIOVsErIhABCpzV6rtmWNIIglYxhs2NrGcilnta1inPNvm3D/fwHwXzLu+xsAf1PHcRFEHtv7Fo6vGNBVBVtdA7sDG54fDSMff7wZ+mxVgev7kXIm05pUc5bLwHbR1hWYjo/dgY2zG51FHxJBEA1BBmedREMATQggiCVie9/EydU2AGCzZ8Dn+WnF7X0TtutX4kXm+xw+R9gQ0DM0KIyUs0n0bQ9ngoBsjzo2CYKIQTVnBHEE2N43cWqtBQDY6hkA8oefyzTowCmvnjm+WCxkTYSiMKy2aUrAJPqWG6pl1LFJEEScMDgbm61JwRlBLA3b+xZOrwfKWVcEZ1kdm0Pbw35gEDusILXp+UJmj6dQ1zpa+BrEOL7PMbC9KDgj5YwgiBhjaU1SzghiuXA8H9f7VpjWlMpZVlOAtN0Aoo7Bcq8vgjMtHpyRcpaL3BXLtOa8x20RBNFszIRyZixJtyYFZwQRcO3QAufCRgMANrqiWzJLOZO2GwAqsXCQdWsyrQkEwRnVnGUiPc62egbauoI9CmQJgohBNWcEseREHmfFas4u70fKWRXBmUxryoYAIEhrUrdmJtJGo9dSsdER3bUEQRCSoS2CsLZOEwIIYimJRjcJ5ayjq2hpSqZydmUkOKsgrelnpDVJOctEppO7hoaNrk41ZwRBjDB0PBiaEtbyknJGEEuGDM5OBsoZYwxbPQM7mWnNapUzmdaU45sAYURLNWfZyPd9pRUEZ/ReEQQRw3S8MKUJRJtfUs4IYknY3jehKgzHeq3wts1u9gin7X0rPNErCc7S0pptHX3bq8RH7SgSKWeU1iQIYpyhPRqcMcZgaAqshq+pFJwRRMD2voWTq60RK4vNnp6rnN2+1QUADCtIa7pht2ZcORNTAg7ITiMV2RDQa1FakyCIcYaOF3ZqSgxVgePShACCWAq2902cDOrNJJtdI/OCf+XAwl3HewBQyQgnKbMnlTOApgRkMQgaArqGivUgrSlG9BIEQYjgrK0ngjNNobQmQSwLV/YtnFptjdy21TNSuzU550I5OyaUsyrTmvpIt2YQnBXs2Pyb+y/hLz5xvvSxLAtSOVtpadjoGLBdH6bT7EWXIIj5IWrORkMdXWXUEEAQy8L2gRl2ako2uwb2hs5Yzdeh5WJge7hlvY2OrmJQgQmtF4xvUuNpTTn8vKBy9ocfOYc3ffiJ0seyLMS7NTcDX7rdIdWdEQQhGNopaU1SzghiOTAdD7sDJ/Q4k2z1DHCOMXPTyBOtjV5LrWa2ZlBzpitpylmx4GzoeKEj9s1A3/agq6LAV5oGU90ZQRCSYaJbExBeZ9QQQBBLwJUg2BqrOQtHONmJxwe2G6ttdAy1ktmaYUOAOmqlARRXzkzHu6nSegPLRdcQ6uJ6J/2zIgji5iW15kxV4FBakyCaz3YwJ/P0WFpTBEc7fSf18afWWugZWiWzNd0wrRlvCAjSmgVrzm425ezQ8rDSEu+RVM72SDkjCCLAtMeVM0NTaLYmQSwDyekAks1uuhpzeS9Ka3YMNZzfVgapnMUbAnqGBoUVV86G9s0VnA1sF92gniRMa5IRLUEQAYMsK42GB2faog+AIJpAcq6mRM7XTI5w2t43sdrS0Gtp6BpqpcpZ3OdMURhW28WnBAxtr/G1FFXStz10A+VMBtJUc0YQhCRpQguImjPq1iSIJeDKvglDU7Ae1HhJ5AU/aadx5cAMxzx1Da02Kw0gGH5e0IR26HiwXR++f3N4fQ0sFystsfC2g1mo1K1JEAQA+D6H5fqpPme21+w1koIzgoBQwk6ttcDYaGDUMVR0dDVFObPCFGjXUCuarSkWi3jNGRAMPy+gnDmeHwZ4Ta+nqIrDWEMAIFKbVHNGEAQAmK5Yl5NpTVLOCGJJuLxv4tRqO/U+Mfw8aaVhxoKzapQzWQOhq6On5VpbL1RzFq97u1nqzga2h15s4d3oZM9CJQji5kJ20SfTmi3yOSOI5eDKvoVT6+nB2UZXH7ngc85xZd+KpTXVSmZreimDz4EgrVmgW9O048FZsxeeqhjYblhzBkCMcCLljCAIRBvW8ZozmhBAEEvB9kTlLArOdgcObM8PH981hAlt2ZmOjp+T1iygnA3sm08568esNABgo6OPGQYTBHFzItdBmhBAEEvIoeWib3tjnZoSMfw8Cs4ij7Morcl5ebVKjojSlURas1Os5mwkreke/eDM8zmGjhdaaQD5g+oJgri5GNpiTaVuTYJYQrI8ziRJ5SxpuyGDg37J1GY0IWBcOevb3th8zySjNWfNXniqYBC8371EQwB1axIEAcTSmmkNAaScEUSzkcHZyRzlbN90Qxk8GczJ4KzsCCfZaamNKWci+DiYYKdh3mRpTZnG7baihXe9q8N0/Jvi7ycIIh8ZnCWtNFoaKWcE0XiuxIaYp7HVGx2oLedqnliNfM4AlO7YlMpYmnIGTJ4ScLN1ax4Gxr+jNWfzNaJ9530X8Ypf/cBEVZMgiPmT1a2pL8GEAArOiJueyxPSmhuJEU6X901sdPVwN1ZVWtMJlbNkt2YQnE3o2BzcZN2aAytQzhJpTQBzS20+fGkfj1w+wGNXDufyegRBFCevIcDnaPSmioIz4qZne9/ESksbUWDiyBFOsu5se98aGZBeVVrT832oChszwg2Hn0+hnFlHoCHA8XxcPbAy7++HNWcxn7PuqMpZNzIIvv/83lxejyCI4mRbaYjQx2nwlAAKzoibnrhnWRrRzEY7eLyJkyPBmQieys7XdD0+ppoBceUsP+CIpzKtI6CcvfWfn8RX/tL7MtMPYUPAAtOa8j2/78LuXF6PIIjiZKU1DU2EPk2uO6PgjLjpyfM4A+LKmRM83sKp1SiYkwXpw5J1Xo7Hx6YDALHgbJJyZh8tK43L+yYOTHdsdJbkMEhr9lrjytnenNKapJwRRHMJGwKM0XXVCOp6m9yxScEZcdOzfWBmepwB0QX/xsCG53NcPbRG6tNkWrNsQ4BMayYJ05oTas6OWkOADHySQ+clg0CpTKs5uzEv5SwIgh++dNDoXThB3IyYjgeFAUZi0xsqZxScEURzuXpghZ2XabR1FV1DxU7fxvW+Bc/nI8FcVWlNx+fQ1fHgrGdoUBgmOt8PbS/8/aPQECADzJ3D9OCsHwTDcZ+zjq7CUJX5pTWDY7A9H5/ZPpjLaxIEUYyh7aGjq2N1vGHNWYM3VBScETc1rufDdHystPTcx212Ddzo26HtxskaGgJczx/zOAMARWHoGdrEbtChI0YZaQo7UsrZ9Yy0pgyG4z5njDGsd/X5pTVdLwzs76PUJkE0iqHjjXVqAqScEUTjGTjjdUtpbPUM7Azs1GkCuqpAV1mo5MyK6/MxjzNJr6VNVObkLrGtq0dKObuRkdbs2y4MTRmr09uc4/Bz0/HxjJMrWO/ouJ+aAgiiUQxtb8yAFoiUsyaXIlBwRtzUSLUrXreUxmZPKGfJ0U2SrqFhWMH4prRuTUCoQ5OCv6HjoW2oaOvKkWgIkMHZ9Yy05sDyRmw0JBud+c3XNB0RED/v1nVSzgiiYQyD8zMJKWcE0XCkGjVROevquDFwsL1vgjHg+EoyOJscPE3C9X1oKd2agKirGkxQzmSg0NLUo5HWdCcrZ70Ub7r1ro7dAoPiq8B0xM78uWfX8ejlgyPxvhPEUSEzrUk1ZwTRbAZTKmdXDkwc67XGUmldQ62g5ixHOSsQ/A0dD11DRUtXYDV40SlKkZqzXsrnttHRQ0+6ujEdHy1dwfNuXYfrczxymZoCCKIpZKU1STkjGstTOwN88LGriz6MhRMqZym7qzibXQMHlovzN4apthtdQwtNUWdlUs3ZpOcfBAtRW1NhHQEFJ6w5ywjOBrY30gwg2ZhjzZnlBsrZrRsAgPvPU90ZQTQFMyOtGU0IoOCMaBi/80+fxw/+8ScXfRgLRypnadJ3nM3AiPbhSwcjo5sknQrSmk5GtyYglDM5SzKLqCFAOVINATvTKmddA0PHm0uK0XR8tDUVZ9bbONYzqO6MIBpEZs0ZNQQQTWVguzgwHXDe3Nli86CfMgIoja1ghNO1Q2vERkPSqyitmeZzJp5fw2GRmjNDdmseBeUsMKHNUc7SagWlEe2kcVdVIGrOFDDG8FxqCiCIRpFtpSEnBDT3+kfB2U2K6fjw+dEwKy2DVKO6E5WzyActK605yYdsEp7PUycEADKtObnmLLTSOALdmlasISBtE3GYWXMWzNesOThzPR+uz8OaluedXcdjVw5Kp7cJgqiGoe1nNASI26ghgGgc8sI3SY056oTDsyc0BMj5msCox5mkioYAx/dTZ2sCopu0b7u5Sqcsfj0qac2hLUavOB7HQcr3NK/mDMiuVasKM1jYZdrkubduwOfAQxf3a31dgiCKkVlzptFsTaIirh2KsUFVIbv5yo4cWnZknVjaRT6OTGsCWcqZWnq2Zn63pgY+QemU3ZrtI2Ol4YeBcNoIp6yas/VgUHzdypl8j9u6WEafd+s6AJoUQBBNgHM+seaMGgKIUgxsFy/7+X/EX336QmXPKS8spJy50BQ2Nhg3yUYsODu5mtYQUE23pprRECBrq7JSp47nw/G48Dk7AhMCHM+H53Oc2egAGB9+7no+LNdPrRWUzRt7NXdsSqW0FSz+p9baOLnawv0XKDgjiEXjeByez1PTmrpGDQFEBRyaLga2h4u7ZmXPScqZoG8JtSk5GDeJoSlYCQKBtLRmz1DheLzUye56fmZDgPRhy+rYlMF2x1DR0pQwbb2syL/nlvV05SxUPFMnBEjlrN60pnyP4z5KYlIA2WkQxKIZOuPnpyTs1iTljCiDDKTK1jSNPGegrJQtYl92Bhku82ls9nSoCsOxWP2ZpFPB8HPhc5Y1ISBfOYsvRG1dDT/fZUUqf2czlLNBTpdt11Chq6x2rzN5jG0t+syee3YDn7vWx4E5H581giDSCTesZKVB1IXcoZetaUp7zsMJ3llHnb6d3mqdxlbXwMnVFpSUujAZJAyc2YNd1/eh53RrAtlKp2lHxeltXYEdpAWXFbmwhmnNRHF/35ID68eDM8YY1jvGHGvOYsrZbevgHHiQmgIIYqEMQw/L8TBHURg0hVHNGVEOuUMfVljkLZ+z7rTm2z91AY9fPaz1NcowyCgqT+NpJ1bwzFOrqffJ9FqZANr18qw0pHKW/vwyKOwGPmcAljq1KY99s2egpSljnZeTJjuIKQE1d2tK5SwWnD33rGgKuJ+aAghioQxzlDNATAkg5YwohcyLDytMQc6r5uzH//w+vOVjT9b6GmXo295EjzPJz/4vz8V/e82LUu+TC8AkF/88HC87rRnVnGWkNYOgrW2oYZptmZsChnaUMjzWM8bma8r0btZMVDFfc77dmgBwfKWFsxsd3EdNAQSxUPJqzgBRR+yQCS1RBqsG5UwqE/0a05qez2E6fqMNUYe2V7jmrK2rmSnQMK1ZIoD2/OyGAKnuZSln8V2iXIyW2U7DjBXby6HzcQZhWjNLOTPqD85SGgIAoZ7RjE2CWCymPVk5s0g5I8pQS83ZHBoCZKDS5OL0vu0WVs7y6NSc1pQ+bFnBn3nUgrPYrncrRznLCqw3ujr2aq85k+peIji7dR1PXB/U/vrEcvHk9QH8Ja4DXTYmzU1uaQrVnBHlqLpb0/d5mCqt0+dMHm+T25UHlle45iwP+RxlgrPcCQFSOctQOmUaUMzWXP60ZlTPpWCrZ+DGIKMhIDetWXfN2XhaE4g6TK8fWrW+PrE8XN4z8RW/9D6895Eriz6Um4bJNWeMas6IcsgvUFVpzXiwVGfNmUzBNV45mzAdoD1LPV4AACAASURBVAjdCVYXRcibENDWFSgs+/OSipo0oQXQ6HTyJOJK4FbPGPM5k39v1me30dXRt71aF98wOEvszA1Nuo+TSkIILu0N4fkcVylgnxvFas6ae22i4GwJqFo5i6e76gzO5AW0qcoZ51zMZ6wwrTnrZ8Q5Fz5nGcEZYwy9nOHqSRNaoNlB8SRG0ppdAweWOxJoSeWsm7Hwrnfl8PP61DN5XibTmsvgoUTMF5niXuZSg2UjviamQd2aRGlkzVlVylm8CHIeac2mWjpYrvACy+r4m4ayaU3pSZbVrQkIlSirGzS1IaCh73sR5FDxlq5ga0UEWvHUZt920daVzPdrMxh+XucIJ9MRg9mTTRzhaJiGbkqI+RMFZ/SdmBfDCQ0BhqY0+hyl4GwJkApIVQ0BcUWlzm5NebxN3Z3I48vyypqGtq6Asdm7Nd0wOMseI5WnnIXWE7oaKjnWEu/SrYRyBowa0WYNPZdsdKRyVl9wNrQ9tPXx0V+knBFJ9kk5mzuT0pqknBGliXzOKkprBoqKqrCa05pSOWvmCRDVLZVXzhhj6OrqzAF0GJxlpDWBQDnLsdIwNAWqwo5EQ0Do26aJmjNgNDgb2F5ureBGoJzVaadhul763D5NfIZN3pUT8yVUzpZYzV424mtiGtStSZRGKl2258Ot4Mskn2+za9Sb1gxc65u6O4mUs/LBGQB0DG125Sz4XDUlJ61paJnB9NB2Q/n+SFhpuFHKMC04m6icBcHZxd1hfcfo+CNzNSWGKt5/p6Hfe2L+yOBsmetAlw3T9jJTmkCgnFFwRpQhXrNVRd2ZfL6tnl6pd1oSmTJtqnImA50qujUB0bE56/spO/uyTGgBkX7NU85kY8ORCM4cP0wZpgZnEwbWn93o4BknV/Bn954H5/V0TZpOlnJGNWfEKGFwRsrZ3Bg6+cGZoSpw3OZ2VFNwtgTEg5sqgjOZ7jrWa6Fvu7VdvMKGgIYGCVUrZ2WCM9kQoOYoZ71WjnLm+DHlLEhrNjQoLkI88NnoGmAsqZzld9kyxvCdX3on7r+wh089VY9bv+n4oW1JHBlgN1UxJuYPNQTMn6HjZ3ZqAqJxp8kbKArOloAR5awCpStUzlYMcF7t5IE4g4ab0IbKWQUNAfJ5Zk1rytqH2RsComBGNgQsu3Img01VYdjo6Imas8kD67/xhWex0tLwBx85V8sxWq43ZkALkHJGjENWGvNnOCGtaVBDAFGW+BeoikBKKnHHgnRRXU0BA6fZ45vke1lVcNZraaUbAvLSmnlWGqbjhbtERWEwGj43bhKm66EVC3w2ewZ2BqPK2aSZqCstDf/ri27FX993CddqMP80HW/M4wygbk1inL2hWAurDM4euLCH9z6yXdnzHTXia2IahsYavYGi4GwJqD6tKZ7jWK8FoD6vszCt2dATYNJ8xmnp6NnB0yQ8f3JDgFTO0tLQg1hDACA6kZZ5l24lAp9jiSkBouZsclD9mpfeAdvz8Scff6ryYxR1cdnKWZM7wYj5sl9DWvO3PvA5/NQ7Hqrs+Y4ahWrOGnyOUnC2BMSVp2rSmuL5pLlnXV5ncZ+zuurayjCsQzlzZk1rFrPS8Hl6g0WyvqKlq0td35IMfDa7o/M1B5ZXyDz46SdX8D894zje/NFzlXQ6jx7jhIYAUs6IADnntUorjaHt1trQtezESz3SIJ8zojSW60H6XFYSnIXKmQjO6lLO4vVXTZSPwxFAlVlpqDN/Pq43eUJANPx8/PMyE7vEtq40thGjCMNE4HNsxcD1oObMdn3Yno+Vgl223/HSO3Bpz8R7Hq42BWS66TtzndKaRAzH88M5w1VumEzHh0nBWSaT05qknBElsT0f6x3h2zSoxEpjTjVnsYWjifVPg2AEUJZJ4bR0dXVmFdL1JzcESIUvbbecLH5t6+pSG14mVanNroEbfTuYhyobOYoF1V/1RadwdqOD3/9wtY0BWd2amsLAGKU1CcF+bEpFlVYapuNVNtLvKCLSmtkhjq4qcDwO329eVgeg4GwpsBwfG0FwNpyxGzBOaKUh05oVPGcaI8FZA1Ns/QIdf9PQbWkYOt5MJ3uRCQErQW1cmtI5TOwS27qy5GnN0U7IrZ4B1+fYN91QhShScwaIbs/XvPQOfORz1/GZ7YPqjtFO79ZkLGjIoOCMQNSpqaus0nXQdD24PqdNQAZDx0MrpWFHEtaG+s18/yg4WwIs18d6MF+wKisNXWVYbYuAr+6GAKCZac2BlT8CaFqksjXLbtYpMiGgJYerpwRnifqKtqYudUOANKGVSCPaG30bA2s65QwAvuWLb4OhKfjDCm01ssY3Ac1v0yfmhwzOTqy0Kj0n5eaL1LN0HNcPA7A0mt5VTcHZEmC5Hja71aY1W5oapclqawiIgogm1j/1bRddvTrlrJeTdpyEW3BCADDewOF6ogZrLK3ZwPe8KFYi8JHB2fW+HSpnK1N02W71DLzyeWfw5584j32z/LxNz+dwPJ5qpQE0v56FmB8yODu51q44OAvq2KjuLBXbmxCchV3VlNYkZsR2o5qzKk5E0/HQ0pQwpVencrYaXEAbqZxNGJ49LR0jW9maRDQhIK/mLP355SSA7pFKa/ojgU9cOZvVPPjffekdGNge/upTFys4vmAwe0ZNS9M7wYj5IYOzU2utSqd2kHKWjR9snoycBqumN+5QcLYECKVLET5aFVlptHUVisLQNdQaTWg9rAeKXyNrziYMz56WvIL9SUiVRc/r1mylK2cyfdxOWGks8xy/tJozQIxwkt/Xaf3pnnfrBgxVwYUKhqFHwVmectbMHTkAcM5xIzZxoYkMbBd/+8ClRR9GafbD4KwdKK7VrIUyG0HB2ThSDCimnDXv2gRQcLYUxNOQ1aU1xUffa2WPBCrLwPKwGdTKNVY5q8jjDCgXnIUNAbndmhnKWfCdGDehbd57XgTH8+H6PDWtuTOwS0120FUGp4KdslRAspQzQ2u2cva+R6/iJT/7DyMjsZrGOz99CT/w5k/g/I3Bog+lFGFac1WYfleV2pTd2FXUIR815PWmlROcyRKSJjoJABScLQVWkIbsGGplaU25a1hpaTisoeZM1kFtNFg5G9iTRwBNQ1bwVITpujUTyllKcNZeYuUsLWXYNTS0dQU7fTtMw09TcybRK6oFm6Sc6Q0fn3Vxbwjb9XG9hrFWVbE7FIHjjX75GsFFsjd00NYVrMnSlArWQlnzCJBylobcGOUpZy1SzoiyWK6Pll59WhMQqbI60ppS4dsIlbPmLSAD252bcjawXfzxx57MnJTgFujWbOsKGBsP/uTrdYzod0W3ZjMXnUnI404GPltdAzt9O/I5myU4UxXYFaQbZXCW1arf9IaAZahXOjDF57w3XP7gbL2jhzWUVShn8edY5safugiDswI1Z009Tyk4aziez+H6HIYq0ppVLKZSiQOE63wdDQFSat9ssHJWZHj2NETB2fj7+c5PX8J/fNv9ePzqYervRhMCspUzxpiYr5lRc9aJdZ6KhoDlXLSzVKmtFSOoOQvSmjmjWbKoap5eFECmL6GthjcEWEuQEpPBWRXdtYtEBmet4LtShaIaP7eHdnO/Z4tCnnt5NbxNH7NGwVnDkV+clq6grc8+HiiO6UbO5istrR7lzB5Vzuad4vF9jj+956nME8/zOYZO1TVnMq05/hk9cb2feR8QpTXzFhPxGmp2zZkxmtZ0fV75PMl5IAOHZHC2GVPOuoZoaJkWTWWVBGfWpLSmxhpZZymRm6Uqaljr4sgpZ3qFyllsXWuy+rkonAINAWG3ZkPP09qCM8bY7zLGrjDGHsi4/9WMsfuC/z7MGHt+7L4fYYw9yBh7gDH2FsZYu67jbDryQtXSlKAhoHwgZTke2vGGgFqCM/GcUjmb9+7kgYt7+LE/uw/v/8zV1PvlglZpcBZ0U6YF0E/uiKLmrCBVjm+aNEpKNHAUqTkTn2+VrfvzIlSlEgvrsZ4R1JwVG3qehq4qoUpZ6hjd8fc8TlUKXV3I72GTPbIOLRGULX9w5grlTJPKWbVpTQrOxrEK1JzdzMrZmwC8Iuf+zwP4Ms758wD8ZwBvBADG2FkAPwzgxZzz5wBQAXxrjcfZaOSXTHRrapUoZ3ZMOUu72FdBpJwFac05F6fL188qeJ7FZX4SMs2WNl9TBmdZu2ZZ3Kvn1JwBgXKWCKajtOaocpb3ek0mK6252RPzNQe2W3h0UxJRc1ZlWjO7IaCpiz4QnY9V1LDWxVFRzvaHDtZGlLNq05pNDrAXRSErjbDmrJmWN7UFZ5zzDwDYybn/w5zzG8E/Pwrg1tjdGoAOY0wD0AVQ3jWyJt74gcfxU+94sLbnj3edVJbWHKk5q6khYMFpTfm+7QzSrQLk8c16kU9DUxUYmpKqbobKWcbC7BUYfA6kW5/I1FQ70RAALGtwlh74HOsZOLBc3Bg4MwfVRkVpzdBbbkmtNJahIUDWwu4veXBWS1rTobRmHmE5EJnQluZ7ALwLADjnFwD8IoAnAVwCsMc5f/cCjy2XDz9+He95eLu250+mNStpCHD98KLSa2kY2LMN685DDmiXA9sXFZxlGW3KAKdK5Uw8nzo2Dmtv6GB3IC4wZoaCKHdvE9OahjqmzJmh71f0t1RZfDxvhk564LMZeJ2dvzHASgnlrJKGgIy6OImhVaPQ1YVcV5ocvB8F5cz1fBxabhCcBaUGFShnFqU1cylipUEmtBNgjH0FRHD248G/NwG8CsBdAM4A6DHGXpPz+9/HGLuHMXbP1avp9UV1Yjk+dg7rM3KUJ7L0OavKSkNaAEivqKqNaJPK2bx3J/LCeGOQvrCHylnVwVmK3clTO5GJZpZyFs3WnJDWTFHOwmAmthC1llo5Sw98joXB2bBUzZnjVmGlIevilnPwuQzam53WXP6as30z2qRWaqUR2+Q1ueN2URQJzqQJbVPP04UGZ4yx5wH4bQCv4pxfD27+agCf55xf5Zw7AP4CwJdmPQfn/I2c8xdzzl984sSJ+g86geV66NtebRfBsOZMV9HRVViuH85hnJWRtKYMzio2oo2nDY0FGHJOVM5kzVmFaU3xfBqGibTmuetRcJalnLm+D8aKKWdJZW7oeDBUBVossKtylz5vwuBMG+/WBMRnO3PNWUWKVuhzlpPWbOqOHIg2CU1WXSIrjXommMwDGViud2NpzUoaAvzYz839DBfFNOObmqpwLyw4Y4zdDhF4fQfn/DOxu54E8FLGWJcxxgB8FYCHF3GMRZBBx42M2qayxM30ZGdh3sno+zzT6BQQMnt8NI68yFXtdTaMpdpaC6i/KVxzVkNaMxnoPllEOfN57nSA6PlTlDPbG0sBys/XWsKFOxyNZIz+TcdWjPDnWT83XanOSoOx7PEwzVfOmu1zZrt+uLYuc83ZbrD+xNOaVXg+ymuAwpodYC+KQj5nN2vNGWPsLQA+AuBZjLHzjLHvYYz9AGPsB4KHvBbAMQC/wRj7FGPsHgDgnH8MwJ8B+ASA+4NjfGNdx1kWuYBcrym1Gdac6UroY5WXivju3/84fuodD2Xen5w5FqY1Kw7OBrEOQkNT5t6taXkFlbMKrTTk8yUveE/u9NELXifTSsPzc6cDSHotkTaNB+BD2xvxOANQ6S593mR5iEnlDJh+6LmkOisNMZ9W7B9TXqfpNWdSOWtocCY3i4wtd1ozVM469Shn6x29sZ/hIikyIaDpNWfVygYxOOffNuH+7wXwvRn3vQ7A6+o4rqqRQUddA4QjKw0ltErIU84e2z5EXtbTckaDs15twZmLlqZAVRha2uLSmlmfS5nh2Xl0DQ3b++bIbU/uDPD0U6v49FO7uVYakzo15fN7Ph8ZwTV0vDG/raOY1tzoGmAM4Hz2z63K2ZpZzQCA9DkTKnZWALdIQuWsoaqLrDc7tdrGtUOrse8j5xw+zy5HiAdncs2t0kpjs2s09jNcJMUGn9+kytnNggx26kprxn3OiihnB6Yz5oMVJ9llFg3Trl45kxfQRdgKyNfbN93Ui3FUE1ft/qSTopyduz7Ance6gYKYPbGgSFpTfl7x78DQ8dBJpPmW3UpDYVHBrkRVWNj9O7tyVo1zv+l4mc0AQPPrWZreECDrzc5uduD6vLHH+b5Hr+IFP/Vu7GU0HsmU7FpHB2NMrAEVNgRsdPWlPMfrpkhDgKYwMNZc5YyCs5LUntYMBywrubMbAVFvdmC5uQtZqJzpo8pZ1YufCM7Ec7c0de5pzXgwuJuycA5sF0pOzdCs9Ax1pCbMdn1c3B3ijq0uWlr2vEvX90cK+rOQ34G40mk6HjoZNWfLqpy1dTVVKdkKOjZ7MypnVc7WzPI4k68DNHdXHk4IaOiFPQzONjoAmpvafOjSPg4sF49fS5+ZG1fOANFRXaXP2QYpZ6kUaQhgjEFXlbAEpmlQcFaSutOacXlWDrbOOhkPbRecZwdvwKgSB9TYEOC4i1XOvOg9SlM1+5aHnqFVnirpGtpIoHtxdwifA7dtddEOum3TcDwOvYBy1kuxPkmvOatuVMy8GeakDGVw1i1Rc1aFI/jEtGZYz9JM93G56WvqhV2uR7duNjs4u3ogJpBc3B2m3r83dNDWlXC9betqZT5n0l6Jas7GKVJzBgiT2iqsdeqAgrMScM7Di21WV2BZohqxKK2ZdTJKCT1vHJMZU+KAqOutjoYAGZwtsuYMSA+cB7ZbuY0GEDUEyIL9c0Gn5h3HeuJ9yLgYej6fUjmLnmdgj9ecRT5nzdwV5mE6/thcTUmknM0WnGkqg1PBd9GM1fyl0fR6luanNcVadjYIzprasXk1GA934UZ2cCZVMyAIzirYMMma005Fwd5Rw3ZFacSkNVU07jTzHKDgrASi4Ff8XJcRbeRzFqU1s3a7MhWQt5OSzycvLF1DBWP1BGcymGzpi6s5A9I7Nvu2V7mNBiDeT9fnoeIpbTRun6ic+YVqzqI09GhaMxkoRMXHzVx48jBdD+2MtGWknJVIa/pVNQQsbyeY/F409fshlbOmpzWlcnYhRzkbDc6qSmt6YZNYXqbkZsX2/NyUpsQg5exoEk8Z1detKV7DUKNuzazdbqScuZleZ/FxUIDIu/cMDYeVm9C6Yc3ZQkxoPbFzAtJVzYFVj3ImC/NlgPzk9T5amoKTq638mrPC3ZrjytnQ8ca6FxVFFB8vq5VGVrG9DM5WliSt2dTxWfK4mpoSkxvNpqc1rxVIayaVsyq+E/L716lopN9Rw3b9idNWAEDXqmkQqgMKzkoQP8nqSmuKLxmDorDJac1gQeM8O51lOqM1Z4CoO6tVOVtAQ4Dl+ji+0gKQpZy56OrVK2eyUF2mlp/cGeD2rS4UheUuzMKEdvLpuJKinKVZaQCi+LgKw8t5k1dsL73OZrbSUBV4Pq9kykZut2aDR8NII2ogvz51keybDgxVwYmVdvDvZh6nVM7OZ6Y13dHgTFMrawho60pYw1b1bORlxwp8CCdhqM31I6TgrATxosM6fc5kIDU5rRntLrNmZVqhlUb00fdaGg4rXqSHtoeuvlgrjZWWhpWWhp1+WremV5NyJgNo8X6euy6CMwAFujWL+ZwBo2nooZ2eBhQL9/LtqvNUqbuO96ApDCdWWzM9t66J97hsunFit2aD05ryYqQqrLH1Soemi9W2htW21lgj2qHt4cBywVh2WnN/6GAtFpy1dKUanzPXC2vOgOYqtIvC8fyJzQCA2Kw1cQMFUHBWCnlCnF5v48bALr0bT3+NaA6m3KlPSmsC2eqalaKcrbS0I9kQYGgKNnt6arfmoKaaM/mc0sX/qZ0Bbj8WBWfZEwKK+ZzJ7lqpzElD2lTlbFmDMzc7OPvKLzyJD/3EV+Lkanum55YLdvngLD+tGTYENDA4k2vARkeH7flwG3iMB6aLlbYGRWFYaWmNbAi4FjQDfMGJFRyYLvbN8WNMbQioqOasramhhc60qc2ndgb4ml9+P64kDLOPCnL9n0SrwTNwKTgrgVShbllvg/N6dneWE8mzIjWWrb7Epf8s5cyMjYOS9Izqg7Oh7YV2B4ux0hAn51bXSO/WtNzKpwMAozVh1/s2+rYXKmcirVnO56ytiQYOaTQsvwvpwVk1u/R5kzYrVMIYw6m12QIzAGEAXLburMiEAKCZac24gSnQTDuNQ0soZ4DwCGticHYlSGm+4LYNAON1Z67n49AaTWtWtVE1HX9kpN+0n+HDl/bx2JVDfGY73Z9t2SkanJFydkSRO9Bb1sXFYqdvVf4aya4T4aOVHkiNpDUzCvzlMbdHas60zMfPguv5sD0/TGuKmrMFKGeqgs2eke5zZnuVTwcAIv+toePi3HVpoxFPa5ZTzhSFoauroXImF+WkzxlQXdv+vBFWGtUHzoBonQdQWi0yXX9kg5OkyRMC5Bog6/eaGJwdmE5YX7ne0RuZ1pT1Zs/PCM7kZrk25UxXoxFuUzZ2yOzLQYradxQo3K1JytnRRAYctwTt3nVMCRDKWXShEq3TWWnN0Tqk1OeLWXNIVlpqptI2C4NEwLAI5cxyJyhndv3K2VMxGw0gXzlzCvqcASIAlAG6/JzTGwLUpWwIsHKsNMpSRbrR9zlsNz+AbLLPmVwDQuWsgR2bB6aL1bY4vrV2Q4OzIK35wiA4S3qdJacDANVZacR9zoDpLVGi4KyZjRZlkZvzSZBydkSRF9ozoXJWQ3DmeiOBVMfI3nntF2gIkL8b/+J2K645G1hyqLgc3yQ6YubZURTVnBlj3Zq268PxeC3KWSe2kz13fQDGgFs3iyhnfqEJAUAwIsoa9alKU85a+nJaadSpnEU1Z7N/F5NegWm0GtwQYIVpzSYrZ6NpzUYGZwcWGAOedXoVhqrg/G6B4EyrxjRW1JzNntaUm7u0OrmjQNG0pqEpsBs6xYOCsxJIVeL0ulDO6rDTSLYE5ylnB6aLY4EPVFbqUypKSiwQWGlplY5vkq/djZnQAvNN8cid01bPQN/2RhQreXxpalNZ4iaxT+4McHqtHV7E85Qzz+dQiwZnMeVskKOctSq6EMybSQavZdAraAiQAXHeMS6FctZprnJ2aLlYjaU1mxhEXD2wcKxnQFcV3LLRxsXd0eL6dOVMrAFZPpRFCX3OSqY1m2pRUhbLK+ZzZqgK7IZuYCk4K0GY1pTKWQ1pzeQOIG+W2r7phMXSWQFcvPtT0jM0mE51XVthwCDTmur8DTllzYGsq4kPP5f1Wr2axjfJ13hyp4/bgpQmEClnaQuzU3AxARCYBgdpzQkNAVnjopqK9ODKU6XKoFfgP2aGdjSTTWibGJzJ4HIz2Mg1LTjjnAcNAUFas6M1VjmTXopnNzq4cGMwcn9WWtPnVTSkRD5nwPTKmcysNLnm7C8/eQFf8rP/kGnwm4dd1OdMq8aUug4oOCuBVEFW2xpWWxqu15LWHK056+Y4Qu8PHZwOAsVBVkNA4vmAcXuGssjji5Qz6cUzv4uADGq3emJhjKech6GyV31as6UpUJi44D25M8Ad8eAseB/SFETXLzYhABCjiwaJhoCm+pxt75tTqR5mmDKsSTmrIN0o1cg85bXJPmehlUZDuzUHtgfP51iJpTVNx69t/XBmLLm4emiFfntnNjpjXmd7QSYlqZwByC03+K33P44PPnY1837OeWg3I9fYqWvOrGbXnP3Jx5/Ej/zpp3Bpzwwbq6bBKdgQoKuskRsogIKzUoTF9Zqa2RVY/jW8qdKaUjnLqzlLXvhkV1RVdWfy+MKaswWkeGQ6WNbVxOvOZL1WHcoZYwxdQwTq2/tW2AwAxOddpgRn3hRpzZj1iWmPBsJx2roSBjuL4rvf9HG8/u0PFn58lDKsSTlTytecTZPWbKI5aJTWbGbNmVSF4zVnwGjDU1V4Pse3vvGj+JE//dTUv3vtIArOzm50cOXAGlnjpHI2akI7OZj6zfc/jrd98kLm/bbng3OE45uAo9Wt+QcfeQI//uf3485jPQCzzX8t2hBA3ZpHFJkyammitqmehoBEzVlGWpNzjn3TwWZXR0tTcrs1x9KaFQdnw4yas7mmNV0vrDkDRusB+zUqZ4D4jD6zfQAAoQEtEAUcaQqA6/th4DCJrjGunGV1azZBObv3yRuFHy+/t7VZaQTqZJkUvnzPWwUaAhpppZHwOcva7C0KGTDITaMMbupIbf7xPz+Je8/dCDuri8I5x9V4cLbZAefA5b2o7mxv6KClKSMbjbacuZpRC8o5R99yMzMfQHwEXzRvedaGgKYpZ7/9wc/htW9/EF/9RSfxa9/6QgCzfT/J5+wmJ25LcaxnzM1KI+1ENB3Rgbja1oVvWVZDgDOe1pSLYFVNAX1rVM1ZhCFnsuYsrpzJha+OCQHieVU8ejkIzlKUs7SFuejgc0D60hWpORPBWdni4zIcmMLvrWhq00oxSa4SvYKgKVTOClhpOG7z6lmSVhqLDuCTyIBhLaw5qyc4u3Zo4Rf+9hEA0wcA+0MXtufjRKzmDADO70ZBXnI6ADBZObOCTvI8ayMrpi7PWnPWRCuNX3/vY/jpv34YX/fc0/iNV78otnmY/hin8Tlr4gYKKBCcMcZ+njG2xhjTGWP/wBi7xhh7zTwOrunIRU4qNHWkNcdNaNOVM3nxW+toQlnJrDnzxi58kXJWzSKd9DlbjHIm3jd5gsfna4bKWQ1pTQDoxAr27wikeSC/9s71efGGgKDmjHMeKU0ZaU2fIxxyPW8czw8/84cv7hf6nSL1XGWoxErDmVwXpyoMqsJge80KfIDo4i5T/s1TzsS5s5JMa1acgvu5dz2CoePhuWfXpw5QpcdZPK0JYKRjMy04a+eUNgBR9iIvi2GG3z8VLU0BY1F5Q1EGDWsIeM9D2/jFd38G3/jCs/i1b30hjJjiOHtac/IaYqjLndb815zzfQBfD+A8gGcC+A+1HtWSYLkeNIVBC4Kz6327cpXCchI1Z4aGoeONFbDKk2ytrY+kvcafb9xDKmoIqDqtGYxv1osQsQAAIABJREFUCk6SeSlnrufD5+J1dVXBWlsbCZzle1OncgYAqy0Nm924x1FezZlfuOasa2hwfQ7b8/NNaEssblUQv8A8UDg4q7nmrFIrjfxjFAt/85QzM6w5a6aVRnbNWXWBxD1P7ODP7j2P7/lXT8Ozb1mbOkCV0wGkcnbLhqj1jRvRpgZnExoC5AY573iibmEFjLHMbEoeTVPOHg3KQH7mG58TmnHLzEudaU1DDTawDQzQigRn8tv1dQDewjnfqfF4lor43MutngHb9SvreAxfIzEmppNxcu8NowWta+SkNVOUs7oaAuSxRsrZfC4CUqY2Yp/NzkhDQOBzVpMLvXze27a6YCwKuPKUM2eKbs1ebArB0PGgqyxVdctrQJgH8YX/wYt7hX4nrgrUgaw5KxWcFbDSkK/VxHoWK/YeV+VYXyVyoxmfEABUl9Z0PR8/+ZcP4Mx6Gz/8VU8XdbwllbOWpuLEagsXRtKabmZwllVzdmCJvzFvo5xMq5cNzhZZ9iDZHdho68pIHfCsKVvOxcbVKLCeRt3bi38PkhQJzt7BGHsEwIsB/ANj7ASAoznKfkpE4CS+QLLwPOlGXwbP53B9PmalAYzvdqO0ph6mvdIwnfGGAHlCVNcQINQ+qQTl1VrVgbwgyuAs2Uk7zOlwrAL5vHfEmgGA/GJgz+fFGwJiwfQwZwB3kc6wOpEXGFVhePDCtMpZvSa0pXzOCqQ1AcBYwEzZIliuCOhVheV2fy+KMK3Zqkc5+4OPnMMjlw/w2lc+G11Dy/WOzCJUzoLgDBCpzXhac3/oYL2bDM7khmmCclagISBubj20p/ueybSmHSs9WCQ3Bk5YHyxRFZbb3JZFcnOexyLqoYsy8eg55z8B4EsAvJhz7gDoA3hV3Qe2DMRtLmRwVqXXWTLIACI1KrmgxotoO7qWa0KbvJhHDQEV1ZwlhorPOgT6PQ9t41f+/jNTv75838LPJjFfs297MDSlcI3XtMh0abwZAIgFSwnljHM+3YQAQ04h8GA6XmZ9Vl536Dw4DL6Tzzm7js9ePSwUJBZVpWZFfuZl6vCKNAQA4vvXxHqWuNdhNyiTaBLJ4MwIuhKrUM6u7Jv4lb//DF72zBN4+d2nAQBdXYXr86k+q6sHFnSVjShjZzdHvc5mS2sGNWdFlLMg0Msb6ZfFwPLCwKQJ0xd2B3ZYAxknz9czC6mCFerWbHBXdZGGgH8LwOWce4yxnwTwZgBnaj+yJSBuSxFaNvStCp8/suqQdDJMB+Wucq2tBcpZ9vimpHLW1oVxapVpzXjAIC8E0wQJ1w8t/Oj/+DR+958+P/XrW2nKWbxb03bD1GAdyM/o9qRypqcrZ3Ix0acwoQXEAj6wvcz07KTi47qRtUMvvWsLns/xSNDBmkeoCtRspVGFCe0805rvuv8S7ju/W8lzxTeVbV1pZHDWM9SRzUpVUwJ+7m8fgeX6+KlvuDssOejMUNt09cDCiZXWSNnC2cCIlnMO1/NxaKWkNTW5fmelNd3w/qw6qGTN47RpTc45Bo6Hk2tC9WtC3ZlQzvSx22dRdu1Yo94kQg/OZQzOAPwnzvkBY+xfAXg5gN8H8Jv1HtZyELelONYTX/Qq7TTiJreSrCLJeFqza2iZnZem441ZaTDG0KtwvubAdkdShrOMsvm5dz2CvaGDvj19TYQ80eKB84jPmeXV5nEGRN2vY8qZlr5rdn1xvNoU45sAsfsd2pOVs0WlNeX36SVP2wJQrO5sWHdas4KxSvL9nDQextCq81D6T29/AG/60BOVPJcY/RNc2GdI6dXNoeWE9WaSqoaf/+MjV/ANLziDu45HXdSzGLnGpwNIzm50YLs+rh3a4czKceVsUlozWoMHGY9JTtHo6NN9hpbrw/M5TgeG5Y0Izvr2WFoTmO37GWWcJm/wdC3YrC1jWhOAfGf+ZwC/yTl/O4Dxd/EmJF5cvxmMCarSTsNyRoMMID+taagKWpoS2G1kK2dpF76VmHdWWQa2NxKchTVnBU+Ae57Ywf+49zy2egZ8Pr3yk9w5bXYNmE7U2Tiw3VqmA0jkZ3THVm/k9izlTKbYtMKDzyPlLK/mLArOFqScBYv+s06vYb2j44ECdWehh1NNymYVVhpmoDwpEz6vqtzHLdfDtUMbVkW7+7h63tW1xgVnB6Yb2mhI1jt66QkBrudjd+jgTGB7IQnreKfYxMQNaCXSTuPC7jB1riYQ26AVCc5yNtjx52pPmfqT145TYXC2+LTmjYEd2h7FmaVZI60cKIvQSWBJlbMLjLHfAvDNAP6GMdYq+HtHHis2ImKlpcFQlWprzgKPpOTgcyA9rbnW0YQKZqgYpNhtyGNOKmcAco1rp2WYSLVNo5zFO6m+/2VPAzC9OW7y5AznawaBc9+uVzn7F3ds4qVP28KZoL1ekrUwu96UwVmsgcN0vMzGhkm79LqJWyLcfWYNDxVQzorWc81KFVYaVkx5mvRaVSz623uiVKKq3b3leOG50Q7WiiYhhp6Pnp9r7fLK2Y2BA86BY71RbSHa8BZfZ9KCszOh11lOcDbB8zGuYmUbiSfTmtN13Mq/81RDlDPf59gbjjcEAGLzMK0Jbdp1MwtZ5rCUDQEQQdnfAXgF53wXwBbI5wzAqM0FY0ykzypMa5ppyllmWtMNUwHdlgbOx9Nnjifk7LR0jEhrVmVC644EP9MoZ2/68BNBJ9XdOB54CE1/ciZqzhJTAgaWW1unJgB82TNP4K3f9yVjacp2xsIsa0uKpjW7sUH1w0INAYutOesZIjh7+PLBxKDIdHworHj93bSoCoPCyvucFUm7GhWNhrm0J4rMqzITjneZd3RlagPTutk33bAZQFJFWlM2BR1bSQRnwVpVNMDxfI6dvhV6nEnObgbK2Y085SwwjS2lnKWkNWdQzk6vy5qzxSpn+6YDn4va4CRCFZzuHLKmqDmbtVltHhTp1hwAeBzAyxljPwjgJOf83bUf2RJgJ1SoqoefR+OhYjVnulhIkifjgelgLdht9jICOCusVRi/mK+0VAyqbAiIK2cFh0Bf3hOdVF/xrBN4+d2nwtqtmZUzNdmsMR/lLAt5PMk049RpzbDmTDQEZKUA2xNSKHXTD4JgVWF4ztl12K6Px68e5v6OGaRp44XWVaOVNIfNSyXHqWo0zOV9Yc9QVednvCGgid2ah6YTeptJ1jp66a7C60Gz1lamclbsfbjet+BzjClna20NKy0tN63JmLCHyFoL42pZ1ro31hAwZV3WeFpzscrZjYF4r9IaArp6dolOFslu/TzCModlVM4YY/8ewB8BOBn892bG2A/VfWDLQHyRA4RcXmVaM69bM/mFFWlNPXhMVDA+8nzhwOYU5cyoriFgaHsj3ZCMMRiaMrFb86f/+iE4Psfrg04qWVs1c7dOrFsTiOoBhzXXnGWhqQo0hY29D2Fas6ByJi8mfduDmdMQID/nrLb9ujm03DDAvvvMGgBMrDszU6xeqqbsyBbT8QqlXatSzqR3VlWpl7jXYbuhPmdJ5Wyto+PAdOGVUA9D5aw3GlRleUdmkeZxBoh1TnZsZgVnQDTzNo14oJSVMTBdD6oSGU+3p1XOgnX+xGoLjCFsXlgUcl3ObAiYseasiFXSUitnAL4HwEs456/lnL8WwEsB/O/1HtZykLSlSDrRV/H8QHrNWXpac1Q5S9YsmDk7ipUKa86EYjK6uLY0JdeE9p8eu4Z33ncJ/9eXPz2cRzmrcjZmpdFthnIGiIU0uWt2fLmYFFOLFIUF81Pd/LTmhLb9ujm0PKwGn+Fdx1fQ0dWJHZum44cWIHWhq6y0lUahtGZFDQGXg7RmdcpZVDPXncEjq27Sas5kkFMmBSfP/6RyNq0TfVZwBgReZzeGkbVRWnCmZb/nfcsd2XylkTxHOjnBXhry2rHa0rFiaAtPa+4GwVlmQ8CUm4epfM4qqEGtiyKrIEPUsYng5/pyDktE3EoDqD44S5NnOxkLyUEsFSAd5MfSmjkzAbsttbLB50Nn3HurNSHF86YPP4Fb1tv4/i97WnhbL0MBnETSSmO9o4Ox0ZqzOn3O8mhp48W7XpjWLB6UiAYOUXOWVT/XWnRDgOmEAbaqMHzRLasTJwWYBVOGZdArUM5aRRsCKqk5k2nNqmrOIsVf1is1YYQPIOovB7aXaqUBoFTH5rVDqdCMPvfMytlKe+y+MxvtUDlrxYZ3xxEjs7IGn3s4FfiPZZWZJM+Rjq7C8Yqb6MpNeMdQsdrWSnfBlmWnL9OaaQ0BM1hpTNEQMIvN07wocjX4PQAfY4y9njH2egAfBfA7tR7VkpCcU7nVM3BgupV90Gk+Z1kjLfaHbrhLi7zQRk86K0c5q8rnzPF8OB5HV08GZ2qucrY3tHHnsd7IohNaRsxccyZ+X1UYNjo6dgY2fF8YMHZbDVLOgkW16IQAQKijh5Y74lmVRBYfW4sKzqzR9NRzzq7joUv7qV3EknkFZ7ZbxkqjWLdmVT5nldecxTaVHUOF5/PGpHXkBjFppSHracs0Bez0LWx29bHygWkHbMu5msdXx4OJsxtd7A0dXNgdpqY0gQlpTcvFyaAWLLvmbPT7l9XBn4W8dvRaKlbbemOUs6y05mDKzcM0JrThOLdlnK3JOf9lAN8FYAfADQDfxTn/1boPbBlIS2sC1XmdhTViiWAqmYe3XR9DJ0ohycUmqYSlBXuSFUOD7fqlLwDh0POEmjOpOLpveWN1YKFlxIwFofGdk2jWcGC6HjhHo5Qzd8oJAYAo5JbTKLImBMjiY3NBu8JDyxu5yN59Zg2HlotzO4PM3ymaMixD2XSj5XiFUq/iO19+0ZfKWVUBVLzLXCrx5pSzGetiPxx6np7WLBec2WMpTWD6tOa1AxsrLS21NEJ2bD58aT8zOGvpauY52bdcnFyVXepZJrSjosC0xy/TpV1dw2pba0BDgA2FjX/mgFjbOJ+u4zytHCiL1jIqZ4yxLfkfgCcgxjb9IYBzwW03PUnPMOmfU9WUgCylq5so4j0wR+sbotmLiZqzvIaA2DDtMkRDxdNqzrIXj77tjszjLHNMtjsua291xQgnGbAuSjlrpShnYbfmFLM+ey0V1w7E9yyr5gzI36XXzaHljChnd59ZB5A/KWAeypmmlK05K9itqSrhd3FWhON84HNWmXIWS2tK1chZvEs8EBXEryatNLrlg7Prh/ZYMwAg1iaFTZHWTJkOIDkbeBt+/lo/OzhL2aBJ5Minlqbk+pzFG1KmDbBlulSmNQ+s+pQzz+eZY6gkcuh5mqlzWMYzRWpzmm7NZa05uxfAPcH/5c/3xH6+qXFTPMOSXYFlsTOUrnaiSDIcet4ZVc6yrDRSlbMZi++TyIAwWQdVRDlLBnRiODnLLIzNIulzBojPZqdvR8dXcwCQRbpyFvicTZHW7BpaaA2QG5zlFB/XTd/yRoKzZ55aha6y3I7NeXRr6iWtNKZrCCinnG3vm+A8CChLpGLjxBsCZrn41UlkXJyw0gj+XcZOI0s5Y4xNNcPx6oGJ4yvpQ3LOboiRbZynd2oCQWlDTnC20tLQa2m5PmfxDXbYwV/wPB84HnRVdNCLtGZ9gfnP/PXDePVvfyz3MbsZ0wGA2LVsijUsbf3Posk1Z5nyAef8rnkeyLIReZCNWmkAqMxOI+01APGFjZ+IYSqglWwISNSc5cwEjFSqcov0IFTOxhsC8mrO+paLlRR7i94MY6XSag62ugbuO78bHt8irDQAUQycqZxNU3PWUsPmk7xRR2mvNy8OzVE11NAUPPPU6gTlrP60pl4yrVk0gNRVVjoVKevNzm52wnFYZfCD+rKkctYUrzOZBUgb3wSUT2t+8V3pQVVnCr+3qwcWnnV6NfW+k6utoBuYZwdnmoIrKeek7fqwXR+9loauoWYqZ0krl6wmsSwGsW76utOaD1zYw8OX85uAbvTTpwMAsZTtDMpZsZqzYLbmkilnRA5pKlRodhqkIcq/RpCeSxawJkZayG6b0OdMtmInAq3kwNw48XmNZRhkpjXVTJ8zz+cYOt5YWhMQKdppA8bI5yYKdjZ7Bm70nTDQW5SVhmiMSChns6Q1DQ2yrj5PBVxUWtNyPdieP1ZHcveZNTx4cT+zwLeoh1gZjNJWGtn2JaOvI4rty3hzyXqz27e6ldScRZ3MTVfORr83XUOFprCZgzPP59gZ2GOjmyQdQylsdnr1YHw6gERRGE6vi9Rmmo0GkH1OyrVppaUF6162z1k7reas4Gc4iPlQCv84p7Zu3Yt7QxyYbu6xibma6Z+LXKdnCc70KZSzRW1g86DgbEbSDGI3ugYYA3YG1eTw5ezOZC4+OdIiqjmLbAvaujK2k4qUs+y0Ztmas0GsTTtOXlpT/k4vJWDqtdSpj8nyfBiaMuIyv9XTYXt+2AbfKOVshrRmPJDNaggAZBp1/gtP2HWXCLifc3YdO307VISSiJRNc600OOeFj1Eu/GUCQelxdttWt5oh6omRcLMM/a6T/YyaM8aYmBIwY3C2O7BT52pKunox5cx0POybbmbNGRANQM9Oa6afk4fx4KyVnWYt260Zn+Cy2tbgeLyW4MT3ObaD8/zKQfr5DojgLG06ADDb91OeJ4WUM2U5a86IHMJFLraDCS0b+uPK2eeuHuKX3v3o1C3BaXnz5EiLqMMp+oKn7byy0qRAHQ0BxdOa8kKeppx1jenNcW3XRytxYkrZ/PyNYfi8i6CVUgPmhBMCpqk5i97fvBRba0HKmUzBJT9TOSkgy++s6NzKMoiB5LMpBVaO+jz+Omzkd2bh4q6J1ZaGra5Ric9ZuKnUI3d5oEHKmZlecwaUm68ZGtBmKF5to1jNmWzOyA/ORN1ZrpVGShZBrnO9oOYsUzlL8TkDpkhrxpqvViuo5cvi2qEVfmevHKRnkzjnoiEgI2iWf+c085XTMidZKAoT5QfLqJzFuzZj/6V/624isorrs4xof+v9n8N/fe9ncXEvewcx/hpean1YJ7GQhGnNWCqgm7LzMgsoZ2WHn2fVnOUpZ9GilH5cs9ScJYNamXI+f0PYOKSpdPMgba6eG04ImM6EVjKxW3MBC09cBYjzRbesgTHggYy6s6IpwzLoqjLzLL1wrmGB1GsVbfqX90ycXm9DU1npFCkQTYuI+5wBzVHODkwHWqD8J1krEZxdD0c3ZSlnxTYxedMBJLJjc1qfMxmYrrRFzVm+cpZiTF4wwO7HRr7Ja0YddWfxa92V/fTgbOh4sF1/YkPANJuHtMxJHmVNqeuiyNXgEwCuAvgMgMeCnz/PGPsEY+xFdR5ck0lLawLpwZnr+fj7h7cBAOdzPJ7GXsPxM4Oz+Ml9YDpQ2GjAkaxLE8ecveuPvNFKpjWddJ+zfOUsO62Zt0hlkRacbfYSytnC0prjC7O84E5jQhsPfvPSmu0JFibTYrs+3vShz+Nrfvn9uPfcTubjsoKzrqHhacd7qR2brufD9fkcujVZGBBPiwxuiprQAuVSJpf2RXBWVcu/XLfkGjDLxa9ODi0XK20t9cK61tZmngOZNbpJktzwZpE3HUAivc7yGgJMxx/LokTnjCoyHzlWGvENdtsQn2XRAHtoezHlTPx/1nRxHpd2h+HP2xllDNHQ84zPZUpVEEjPnORRlVl01RT5C/4WwNdxzo9zzo8B+FoAfwrg/wTwG3UeXJOZRjm759yN8LYLsS9skddIq21J+pyJuZr6SG1amnJm5XSxzDrHMskwo34sVznLSWuuzDC5wPZSlLOxtObirDTGJwQEJrTTjG+KB+K53ZrVpDV9n+OvPn0RX/3L78fr3/EQHrtyiHvP3ch8/KGV3nUHAM84uYpz1/tjt+c1rFRJGSuNUDkrlNasQjkb4pb1dnjOlg/OMhoCGqOcjc/VlKyXqDm7HqQjsxsCig3YvlogrfmFp4U6fPuxbur9ck1PrgNRnaaeO04v2S0c+pwVNqF1YzVncmZpzcpZRlpTjtTLCs6mnd4AZJcDZVGmzKFOivwFL+ac/538B+f83QBexjn/KIDsb+gRJ63mDAC2eq2x4OzvHrwcfllkcFDoNVwvNZCSC4ncee0PnbEFLbXmLDCfTNuVtjQFmsJKK2dyQUmmptK6FKPfyU5rpgWZk7Acf+x924ylNRkrlpaqg7TxTWFDwDQ1Z7H3Kk/FyZvjV5QPP34Nr3rDh/DDb/kkuoaK3/uuL4amMOzmNL4cZjQEAMCZjQ4u7g7HlIMo8JnH+KYZlTO3+DGWVc4cz8eVAwun1zth/Yxb8iKSVPyjmp6mBGcOVlrpilOZmjOZ1syqbSo6w1EqZ8cyfM4A4Pm3beATP/k1eOapdLsN+d4nMwlyQ9NrqZk1Z57P4Xi8VLfmMNatuVpjWvPS7hBtXcGZ9XZmQ8BuqJxlqIxTNjsA0wdnRkUzcKumSOHNDmPsxwG8Nfj3twC4wRhTATTvL5oTWWnNY8GYIN/nUBQGzjne/eA2XvaM47jv/F5Y81QE2/VTi/fjIy3auop90w1NGuOPuZaw9IibTyZhjM3kKZZkGBR0JztM8wafxwthk8wy8zNNOVtra1AVYWjbM9RUN+p50NKUYIH1Q2UlstKYsVtzQs1ZloVJER6/eohX//bHcGa9g1/6t8/Hv3nhWdH40tXDlEQaYf1ManDWRt/2sD90Q+d3YLp6rjIY2uxWGlFas7hyNmtDwJUDC5wDt6y34QeBbGnlLNGtKd3xF2VUnGSScrY3FLYPReuJJDt9G+sdPbOus7BydmBhq2dMrA/NCgKBKJgS52X0/Y9vaHqGBsv14Xr+iMVO2gZGV4VZd+HxTSM+Z1I5qyGtuWfizHoHax09s+ZMGrbnBc3AlMpZyvqfR9lxbnVR5C/4dgC3AvhLAG8HcHtwmwrgm+s7tGaTldbc7BnwfB52vzxwYR8Xdod4+d2ncXazM31aM63mLPGF3Ted0EZD0kupochqMJCIFGLZhgA3tRNSuqWnFTSHac00K40ZZn6m7ZwYY+HubFGjm4D4whz9PZGVxvRpTTXoNsp7vTLK2RPX+uAc+PVvfyG+6UW3hnVxG10jHFicRujZlHKhPRNYDVzcGz0XzAw1umrKFABPE0CG7uMzvpa00bglVnNW1uvMDLs1xfFP645fNwemO2ajIVnr6PB8PtOxXu9ne5wB09WcZXmcFaUdpiGTac1ok5rljB99/0bPkbZeLLgExHWjOwfl7OLeELdstHFytZWpnMngLKshQFMVGOq4LVQetutP1VzVVOWsyODza5zzH+Kcv5Bz/gLO+Q9yzq9yzu3/n713D5Yky8vDvpOvet1b99V9+3b37Zme6d15MLs7+14WSYswixYQIECAWK0IbIN5OMKBwhGyhMMSyHLYIcvhsPkDCAJjRciWQhZGwiaMEDYGwtqFZRfQsq9ZdqZn6Jl+3b7PeuX7+I/Mk5mVlY9z8lE36978Ijpm+tbtqqyqzJO/832/3/dRSr+6jINsIoyE/EZgMSXgX3/hAWSJ4KMvXsP+Vl9Q1nQTJyvj3i+erDl/cvc7iwMB8diPOIp4isUxNZOn7dj7SLoIsmRNxhClRZkkwbQXZU0g7Gs4r9BzICw8okxFEeaMnQM9Vc5kEbqK5Ie9F5PDGDsWb6Te7KmZMWUjZvabcC4ExdlJvDhbnqxZtueMx+eMNSUXnQxlBrTXN3qRnrOSsmYC88fLGi0DYyObOQOKpQQcjZOjmxh6qgzTdnOnYbNyNXnBPvu4ncbYsNFRJKiylLruhX2Z8+dfj7O31LS9oRu2fqxpCgiphzl7eKpjb9jDtWEXj9KYs4n3upu9LKZREhpYsZzk9T8NagkmvU7wWGk8Rwj5BULIvyGE/Bb7s4yDazLi8gBDkBLgF2e/8YVH+ODtbWwNNOxveb02vOPwhu0k0rO9wDXZuwGOEmTN+NAAe76sHf+gI+4pFscssiuLIivDbBLkcSYxZ+LJBUYKrc2o8/PyOANCxmWOOXMLDAT4i3fWpCbgFRGUFmdcToKdbaw462vZPWe6lxGYJB/f8K0G0oqzuq00lBIJAUKyZmnmzCvOqp3WXGT8e5oMvTHMmZXItgIli7OUXE0GXrPTg1EFxZmS3EfFcjWjxxNv6TBSNjA9ja9nbhpbayWJYE0rPgWbBttx8ehMxw2fOTudWYnF4/HUxFpHyZQh+9oi0ZAFo0jPWQOLM5671L8A8PMAfhFAM67gBiBc5NKLs68+HuOrj8f4ga99GgCwv9WD5VA8Hum4vtHLfQ0zR9acmd4xJMmaHnPmBL1vgG/NkXFTKeIpFsc0pTgLmmBjfRaAx5z1VDnRSqKIOW7a58YmNs8rHQBIYc78hUHESmMQYc4yX09hr5fMwubheGpClsichx7gNfB+/q30m+TEsFM/5ysDL3/wrZN5qUPEpqIMtBKypiEyEFByWvPBqY6+JmPYVQLpuqz8ktQr2xRZk1LqM2fJElcQfl6gODucGHjv05upj4etInZinyQ7vkqKsxRZc6zbQWHKjiFJ/fCeY35963HKmknZwl6EU7XF2eORAZd6rC8jsQ5GBm5tz0+wZoWeM/RiiTh5KDSt2UBZk6c4symlP1f7kawY2JcZlzfmi7OHAIC/9NI1AGGsx1vHM67iLK3nLBwvtuG6yQvaILITZAWObjuZN+iBpqQ2bvIiq+cMSG6OHhvJuZpANPNTRNZMZhybwJyxzz86qRVYaQhNa/rMWU6REPS4WQ6Q4ruUheOphc2euiCdegMB6bJmlAWIQ5IIrm/08GCh54zfpqIMVFmCS73JN5GCGBBj98qyXQ9OZ9jb6IIQErBw1TFnUVmTP/S7Thi2C8uhlcuaruu50GfKmv6aoJvpn+/YsGHYbgU9Z4sbNMDf0GiMOWOb0rismSyrez1n+edGGK8XfsZe+Hm1sia7tq9vhn5wj0f6QnGW970AfuEpkhDguKlrTxI0RSpNStQBnlXw/ySE/MeEkOvRlIDaj6zhyDKhBbzi7N984SGbbONcAAAgAElEQVRe3t8ICrH9Le/E5O07M1LYjmD83XIwNm1QigVmI8kfxog5S8dRZDIyjnzmbHEB8eJEkm92A60Ac5bSc7A98AcCmtBzFuk3YUWCyAQa6+Xq5ryXtF06L9J2tpt9DYbtpva5eGai6cXgjc3uoqwpwEqVQZmiqYgJbdFpzQenOq77IdpV9Zwl9cz1EnJ4zwOjlFxNhqLF2enMguNS7AzSi6qAObPS1xmedAAehNdkgqzpr+NsPVxkzpIHUnoqnzQdMGeRdcMrzqotTu77rPiNjR52/c8raeN/khF6ziDaE5nWc5yGpsqaPO/gBwH8LQCfBPBZ/89n6jyoVYBhu5DIYlh1V5XR12R84f4p/t2bp/jYO/aCx/Z952heO420njNWXOimE1D8wxgrwnZe0Ys7bcCAYdCRK+k5S+qDyoqyie4YF4+pmKyZyJz1m8CcLXocWa4rzOBIEkFfk9HLYZnSmo95cTyxEg0i2c/S2DOPOUs/125s9IIFnCEofGq20ggkwgIL8kyA3eso5Qqqh6dh+0NlPWcJvbI9To+vujFKyAiOgrVuiPZHBdFNGd5kPEkJ1RVn7JqM+5xFe878dS/eN5wma3IWMIEP5VxxplaerRllzq4NvQ1GUkrA8dRK9ThjEE2JuTSyJqX0mWUcyKqBFTpJbMf2QMNvftGLa/rYS2Fx1lVlXFnTuO000nqnoqxYUq4mEJEDI7R4npVGFT5n6cxZ1NtnHhPDSWfOWHEmGHybdHEyVvM8e86CXXPkc7AdCrWA71pfU/JlzZTmY14cT82A8Y2CsWnHEytRop8YNq6sJTukA97E5sMzfU5aXJasGZjDFliQRaw0yiQE2L4BLWPOyhSUURi269uvhJ9xX1Mws/inyOtCWuQXAyvaRJmzvOgmIJIxmlWc+b6RV0rKmmFrQ4Ks2ZnvOYuvx2kTzbw9ZzNrMcFlvavgq4+rZ87WOgqGXRWuS6FIJDEl4HhipqYDMPRUOSiMeSDqc1YHc1gFUoszQsi/Ryn9LULIdyc9Tin9lfoOq/kwLCe1uX5noOHN4xnetruGO1fX5h67KWCnYaSZ0EYiV9iOZ9GE1p/ojND0ekpWJ8NaR4HlUL+IK1bApPWcZTJnpp26cAbTmoJWGknH34yes0XmLG40yYthV8mUDoFkXzURnM4svPNmkqzp/exklsycjXQ7tY8Q8Iozx50fjhGxqSgDtYREqPvpEzwmxuGEsnhh/GRswnEp9oLirJwtB0PSBq3bGObMlzVTes5kiWC9qwgPBLDopjwrDSB7WrMq5qyTypw5IXMWbK5jxVmK9M/7HbJ1tL8ga1bPnLGNhSQRXF3vLBRnluNiZNicAwH1+ZyxyMUi5sZ1Iusu9fUAfgvAtyc8RgFc7uIshdUCwiLgmyOsGcP+Vg9fvL8Y+hwHC4FOKjKiuzy2oMVlzaSixohlssWx59PP946meNtucvRIHmZWsqyZ1X8zMWzcSmBngIKyZsrOabsBPmfz7uAebH9nKYp/+D3vypUE0pqPeXE8NRPdu9luN81OY2ykm4kCYaPw/ZNwOIadG7VbafifdbGes/RNWRxaCVnzfsSAtuxzRZG0bvW0pvScpeexMgy74hFOgayZ0XPGk+H4ZGx46RgFBmuimBvSiWBsWEErQJozfuq0piZxXeOsgIsaca93vWnNKouTB6c6rm+GjPruemdB1jzJCT1n6HPahDBYgszZ1sDrn51Zzrlu3ONIPRJK6U/5//0Plnc4q4Os/i22Q/tYSnH2m194NGdxkQQmX+QlBLBdZHy3md5zln7SvuPmBgAv1aBIcWb601ZJxqOdBH8vhixZk71X3mlN18+eSx4I8Jmzc0wISGbOqJABLcMHbufP5ZQZCNAtB7rlBo3YUQSyZkLPGaUUk0hzcxKCyeUTHe/znGYwMx1IRGxqtQjKZF7mbXCiKCNFBh5nw+p7zuLrVl9TGsWcxVWAKIqEnx8FuZrpz9vlYM7OZp5Bbtnot6RWA9txoVtusBlVZAkdRVpo58gaCODqOWM+Z+o8c2a7FLrl5vom8uLBqY4X94bB36+udxd6rU9y0gEYRJldQ3AggG3ajybmahRnDISQDoC/CuB29Pcppf9lfYfVfGT1b33tMzt4dKbjHTeHC4/tb/ZgOi6ejA3sDrsJ/9oDk/+SdgDRSIs0WTNpJ+jt+tMvvjtXB+goEj7/1im+8z03U38vDUm7MoZME1ojXQKTJIKBxp9cwG6ESZ/b9Y0uvu/9+/gLb7/C9Vx1IIk5s1xXKLpJBKHPmfjNN8i9yxgISGLODN+FPEvWZIzQg0j/pW55hU/d0kJZWZO3J47dIIpIymE6QLU9Z7q9yPyx6J+8DWPdGGXksTIUCT8/mphY7yqZrRo8AwEj3cosHHmhysTPMw2/S7b5jL73pB7gtGlhVpzlsV/TYI2eHwgAvPdXRXFm2t79LWqjcW3YwWffOJr7vbT0kTj6mowpx3uLvn4WCREHUwaOJxb2t7j/We3gKRN/FcApvCnNciZYFwhZhq7f94Fb+L4P3Ep8jDVX3zueZRZnadmdDJ4jtI2RPp+RxtCP+YNRSr3g84yTVpElvHh9iM/fP039nSywMfR8E9oQlFJMzPRpTSA5iioNWYyjIkv4b7/nZa7nqQtRU1gGxy3GnPEgbWyfByxaJUk67aoyuqqUmK/JGruzZM31ror1rjJnp6ELsFJlUM5KIztlIwpCvNzTIq/z8HSGrioFrEK1zNn8tcGuV8OujjkpgmAgIEvW7Cl47WAi9Lx5uZpApFUkiznLCGUXASHEz7wNXytpGGLQkRfjm1hfZrxvUPOSQAzbzbyGpqYNWSJzzBIbJjvTbewu8gnCeHSmg1JvIpthd72L46k1N6yVtfmLoqfKcJgiomSvk5RS4YEAZrF0lOHbeB7gOdP2KaXfXPuRrBjybCnSELXTeN/T6WV6WjwUA9spnc0s9DV5oaGcFTtT/6K3HApK85ut33FziF/9o/uFdtHBrkwgvkm3XLgUmSyLSCB7FuPYBCT2nDnFes54kNZ8zIO06CaGrb4W7H6jGOthgHMWbm725lICdCt781AVyrBQjN3jRdFQ5Qe+jQZjCqocCEhiXYD0ftFlYaRb6KlyZjP3Rk/c9uFoYuSyM6zgzuo5G+lWJcUZ4K0D0YntaOg5w0BbjNPTfXul+NocpsZkn58Tw5umjzJQwwhzVgXYhivOnAHexCtraeCVNcO4wmRrqShs17vPCcmafi/i8aRZxRnPO/gkIeSdtR/JiiHPliINN7dYr032xGZgcpvCzjHvl7MUqj3eq6WnmObG8dKNDYwMG/c4vdiiYJJAcvB5ssTDFp8se4u+JgdFZh6C4qzA9OMyoEiLkobliE0XiSCt+ZgHrPBK69XZ6KmZzFmeS/eNzfmUANHCpyi0EoWOiKwJeJuEImzXg1M9GNABwoKyloGASHTReWKc06cIFJM1D8dmcANOgyQRP2A7/TNIyjAuiq4iza0BSaxhkr+XkbKB4Zk2Bbw1Oq5SsIKzKjuJUJKPMGd+cRYdCjjmHAjgfW9Asc056zk7XMHi7M8D+Cwh5BVCyOcIIX9CCPlc3QfWdOQ116ehrynY9q028p4fSC8yWNDtSLcXcjUBb7GJxl4ETFwec3bDGwr4AsdEaRwhc5ZgpeG/bpxFCHaMGbKmSHJB05kzJmkYsYSA2mTNEj5nebLDVkr4OW9xdn1jPiVAt9zabTQABCwzC5wXgaj0WtTg8mEkHYA9D+D1J5ZBEuPP2LKiE71VgUc2HHZV6Jab6JeYBh5ZE2B+b1kDAVaqQa4oOnFZM6HfLrnnLPn845FlAW8zHFc2wp6zaoozNml8I8Kc7a57/x9NCTiemNBkKTexJRpXmIci6/96V4EskcYxZzwc7bfUfhQriLRoJR7sb/W4i7O0mxWTNXXbSd3NeY7/jv98fMzZc3trUCSCz791im995/XM340jzG1LkDWD5ui48SIL4s0ozjQZT8Z8F07WQEBT0Intmi2XQq5pIIA1HxdpSs+THbYGKl55OFr4eXCjybnR3tjs4XhqBd54nuTWdFnTxZU1AVlTES/OHJfi0ZkeeJwBUVmzfHxT3AoiOv19nhjr2fYrALDRZ+HnNq6u538PlFIcT0xsZ6QDMOQFwI8q6jkDvDUgek1OEjY0fU1eiDxKK866EVkzCzPTmRsGAELmrKqUgAcnOjZ66twmnTFnj0dR5syLhstr8uctPIHwmhZRIiSJYKuvNq7nLPUdEEJYa+Ao5c+lhpEw9cQLrzjLlg3ziqkekzVn6QtGLyIH6jk9bAwdRcZz19bx+VLM2eLiocoEJKFI4JE1RZILmi5rAt5nPN9z5hZKCOBBUvMxL06mXj9j2iZko5fMnLHvNI85Y70nLMZpZjq1e5wB5fq3DNGeM0U8t+9wbMB26RxzJksEslRsuCCKJGNrHnf8ZcDr6cpmpkTzNc9mNmyXcjFnPS39OnFdirFpL/hJFgXfQEBCz1mKrM6um7zrfGLa6KtpsmZFxVnEgJZhZ9CBRGLM2TQ5Gi6OHmfhCRRXTrb6WuOYs6x38E/9/7Iszc+izdYMUFTWBPxG6OMZKE3fBYfTmhkDAabjjXenLBgDTQkKJiPFWToJ77g5xBfeOs08viSEobqLN2VCSGJz9DihETaOpMbYNBgNlzUBz0AyypzZNcqa3uvJhXzO8hbPrb6Kk5m1cJ7wWCIAETsNXwZZ1rRmGUPXmeUIDS0UGQhgPTt7sVisopOfURj24rSpCDNRJ0a6nXvODAUjnA4nXjGQlavJkJXhODJsULoYk1cUXVWa8zpMWgej6zdD2jXC+x0mMWcDTQEhFcqaJ/pCcSYHKQEhc3YyNTO95xh4DIIZsqb1s7DlpwQ0CanvgFL6bf5/n6GUPuv/l/15dnmH2EwUndYEPDsNw3YzpTp24aYVGX0/0uIso0k1utjkFXtRvHRjA4cTEw8TgmqzMMuQNdlrx5kzNiqe13PGG9/U9J4zIJk5q8vnDGDNx0WYMzPRgJZhq6/BcSlGMVaTxxIB8GRNIJzuEm22L4rSVho1M2cPYukADKos/lxxJFkAiTATgCcV/ug/+Qz+31celzqWOMZGvmzIZM3TlNiwOA6DXM38yKUss9MwlL3uac3w3Op3Fv0d06xceL/DSUL2sSQRrHWqy5d8cDqbSwdg2F3v4lEB5ozHIJihqHKy3dcSDbXPE1zvgBCyRQj5ICHkI+xP3QfWdBhWsWlNYN5OIw3hDiDN50wJEgLSFowoLR764/AxZ4CXFCCCLFkTADRFXpQ1ExalOLzeOZuLySu6c1omuup8kVo3c9ZR5UJWGsc5O1t2ozyZzLMYE8OGRPJjmPY2uiAEgZ2GiIdYGZTtORMpIFVZfFozbkDLoBV4rjiSNpV9QeZMt1z8xhce4be+VG1xNtLzpzXzYsPiOByz6CY+5iztM+BJLxBBV5mXNUeGDU2W5r6bgaZ4hs6R71xP8dfkLWBmZnJE0bArblGSBN1ycDy1cGNj0cPz2nA+X/Nkaqba9ETBYxDMUFjWHGg4mlSbL1oWue+AEPLDAH4XwG8A+Pv+f3+63sNqPtJCyXnAjGiz7DSMoJhKlzVPpiZsl6bKmr3ITpAVAzw3lhevD0EI8AVBM9pphpUGwJiz2ECAyTetSanozun8/Jry0IktzJ7PWX3FZKcwc2ZlLp7sRhnfcbLQ87xGX1WWsLveCVICljWtyXbVtqCsSSkVll6LyJoPT3VosrTgzaXKUiUDAWlWGrzFGWNGi9jtpMF1qc+cZRc/bJiBtzg7Cpgzvt6mtAIgjMmrqudsvrXBS0lJLpqj0XXe95cua3L1nCVsnr3w8/LMWZKNBsPV9S4e+2oMpdRnzvI/zyIDAaLF2c7AY85EW3nqBM87+AkAHwDwBqX0GwC8B8BBrUfVcLBQ8qIFwM2AOcsozoJpzXRZk1kBpE9rhsxZaGqbf8x9TcGdq2vCzNnM8qbt0sxrOwmTa0nmi3EkhbinYSVkzQXmzK3NhBZYbD7mxfHUzFw82WMns0XmLG/qjuHGZi8YvTes5UxrKgVlTdNxQSlf3yaDJ2uKLfgPTnWfVZw/J1SlXM8ZSwlJcpcH+GVNds3mTZyLYGwyZiqn56ynghAk+usl4cjvOeMqzrJ6zvzCpVJZ04rKms4Ca8j67+L5yFkDAXnf4dRIZs684qw8c/QgwYCWYXe9g8OJCctxcabbcFzKJWuyAQaunrOCsubWwGvROJudr9dfFDzvQKeU6oCXs0kp/TKA5+s9rGYjkM4K3kjWOgo2+2qmrBkUZykFYLSvK23B8MxbY1YanMf80o1hAebMzgyO1RJ6zsaGA02WMospVrjxTGyajhO8VlPhMWflg895EW8+5oHrUpzOsntCmMVG/EY5zshKjePGZi+Y1lxefBMzdBX7THgnnudfqxhztpcgC5XtOQvXrZSEAM7ibBwUZ9PKmIYkn68kyBLBsKsubAjScDgxsdZRuM6rXsYmZmT4GcY1TWuO9MUIu36w7s0zZ4kDAQH7mX5+WI4L03ETmbNhV62EObvvM2c3Epiza76p8pOxwZ0OAIj58BXdnDcxwonnHbxJCNkE8K8A/CYh5FcB3K/3sJqNvGglHuR5nZk5zFlUOkxbMOYGAlICc9PwjhsbeHCq48mYP051amRbIXRUeeFGNTXthemhOFjBxzOxuQrMmddzNh98XldCgPd6883HPDjTLbg0PboJCB+Lj6DzOL0z3PCNaG3HheXQpVppiBY6rNVApID02GKxz/5+ghUBUL7nLG0oSJUlqDIRljV1K3uoSQQhM5V/s97sq4mxYUk4mphcrBmQPa3JGJU6fc7ihekgmFIM1z09hV1m32nWd5jVE1yZrOkzZ0mbi911lhJgcKcDAN5mSpYIlwlt0Wl9dhxNmtjMfQeU0u+ilJ5QSn8awN8F8D8B+M66D6zJyAsl5wGz00h/DZ8BSrlpRy+wNCmAOV47LuU2oWV4yR8KEEkKmJpOZmN/R17sORsb2aHnQLibFpI1m+5zFg0+dyjkOmXN2OvxIFw802+WQf9PjMUYJ9xo0nBjswfDdgP2bKnTmoL9W7rgBgdg8U38r2M5Lh6d6Yk9O95wQXGmKislpJtjwBpFlMHO82vkxdhnpniK+s2+xi1retFNfMUZM/Z2E5Ijqp7W7KjecBRjHifm4oYm2JTOMWdu4tAMi5/KYpdmQXGWJGuqlcia90917Ay0xGuEMWePz/QwfYTjuyGEoK/KmJn5a1jQcyY6rTlI3mieJzLfASFEIoR8nv2dUvo7lNL/g1LanHdwDjBTdqAi2N/q480MrzPDdqHJ6f1b87JmekIA4O2mRKw0AM9OAwA+/xa/tDm1nCCkNgnxXivAY9uyCjoAAbPGw5ytis/ZPHNGA6mtrtcTZc7yopsAr3drvassNGePOfyqGJidxqtPxv6x1s+cFTV01QOvQBFZkwjJml+4fwbLoXjnzY3E5yrHnKVv0PoZBqxxRKPU7lXUd3Ym0NO1KZCvyRvdBIQB20lpGiPdRkeRSm3Io2DnEHutsb7YCrAWa+fIG0jJGmgAsg2/17sKznS+ifgseDYai6wZEMnXHIWyJs9AAOD1Rc6s/PXfKsucrYqsSSl1Afw7QshTSzqelYBo/1YS9rd6mFlOKo3qxUOlP/+8rJmWEBA2lIpYaQCeE/dT2318UYA5m5k2+hk316TJtYmZ358UX6SysApWGos9ZzX7nOUs2kk49QuuvJ4QT2KaP4eTJJo0sN6UuwcT71iXYKUBFCt02DUkIr2K+px9+u4hAOADz2wtPFY0p5Mhq2cuL7ooiiiTUxlzxoozjvNmK+GcS8PRxBCSNYHkDMczjvQCEcQzb8cJQzTxTWk4kJJhTF6COXNcWtqI+MGJjr3hIusLeBOREgEOznQcT/hlTSBbco6i6LRmE5kznhX0OoAvEEI+DWDCfkgp/Y7ajqrhqELWjNpp7KwtGiQatpN5gvXmZM20hAB/sTE85kwiEGJoXroxxOcFhgKmpoO9YfoClsScTThkzX7kfeRhFWTNOHNWt89ZEYNJHuaMPR5nzkZCAwHeLvs1nzkrs+ERgSqJS4RFZE3P/kKkODvGM1cGQVB0FJoicceYJSFkzpJlTd4bMzuGrirh3lE1zJlYz1lybFgclFIcTczE9TUJWZYiZ7qdugkuAnYOsXNqknDNDILNtTP3u2nnXzfDp429BpDecwZ430PWUFce7p/O8KFntxMfU2QJO2uh1xkh/AMWeawgQ9H1v6/J0BSpUcwZz7fw92s/ihWDaP9WEliu4JvHM7xrf3PhcTMnHopdYJospV6s0UZ6Zj6Z5z0VxTtubuDXP/8QpzMr0ymeYWY6qekA7FgXrTQcXF3PXjwZCzPmYc5sz5YiTQ5uAjqKDMuhcFyv18zzOavveDd6KmaWA9N2uXeUx9zM2Xz/D6XUs9Lg7M3ZHmjoKBJeY8zZEmRNAFAV8eZ63RKXNTVFgsH5Oq5L8QevH+GbX9pLfFyRSLmeswyvwyKy5tt21ypjzli/E0/P2UbPmyy0HTewRUl8TsOG5fDlagLZGaNe6HmFzJn/Heh+j9vEdBaKs4A5M5gdElNs0mVNPaOAmVrZAwGA9z2w3jBRjA0bI91O7Jdk2F3v4NGZDkUm2Oip3L22vZzCk6HoQBghxEsJaBBzxvMOvtXvNQv+APjWug+syahiWvNmTkqAZ3KbfqPq+d4vWbu5qLOybokHtb90wxsK4JU20wwOGeKxRQCf7UI/Is/mQaQAOS90gn4T77Ow3eybTFkwJ38RB/CTqQmJ5Duib/bmJ+dmlgOXZvvWRUEIwY3NHu4+WXJxVkDWnAm2BgDeEIzluFy9PF95PMLpzMIHnklmHoqkDUSR5XWY5fEVhzfEI+Pp7UHmUBMvHJfid75ygL4mB2x/FraCCKfs85mlA4gMBAApzNnMqixXE4gwZ7YTyJYLsqY67+8YMGdZectZ05pGuqzJrvOzEhObD32/whspPWeANxTweGRwRzcx9DVO5qygrAl458lKTWsC+KaEn31L3j8ihPwSIeRxdKAg9vgnCCGf8/98khDycuSxTULILxNCvkwI+RIh5MMcx7k0hAaxxW8kGz0Vw66Saqdh2NnxUGyXl3XzHAQ9Cw6MlCmfLLChAF6/s2lKNAhDR11kzqZmvqypKRI0WcKYR9Z0ml+cscWVLba2S6HWzJwB/GHRgCdrbvTUXAYy3v/D61cVxY3NbuAsvgwrDaCYZ5hewEpDlSVQisAwOgt/cPcIAPChtOKsANsXRVavbE9VhExoBx0lsANKmm4UwT/6jVfwyVcP8VPf/jVczD6zcMnzOgsMaDlCz4HsgO2RblUW3QREmTM3KL7iGxpFltBVpWBTGg6kpHtfZsqaJp+sWRRs4jqfOTP86Cb+z5O3J9Io0dayMsUZIeTHCSF/AuD5SBH1OULIXQCf43jufwzgmzMevwvg6yml7wLwDwD8QuSx/xHAv6aUvgDgZQBf4ni9paEKWRMAbm71U3eeRg4DxC6w9Qy5MWCcDNsr9gSZs6vrHewNu9x2GrOEUN0oNDmp52yRzk9CvyPz+dxYbqP7zYCwqDdsz+aEUkCucSBgWKg449vZbva1QGICIqHnIsVZZDFfhpUGwDzDxIqK0CtQTNYEwNXI//t3j7A37AbZuwvPVdJKI3MgQFDWXOso2N/uw3RcHAh4Icbxa5+7j5//nVfxiQ89hb/2Ab65szTz4zhEcjWBSFJCwufgyZoVMmf+RtmwnMBGJGmKcqAt5iOn9pzl9GXNMn3OvM+0jJ3GA585S/LoY9gddnE4MXA4NoWYs56mcJvQarIk1L7DsDXQuP3zloGss+2fAvh1AP8NgL8T+fmIUnqU98SU0t8lhNzOePyTkb/+HoB9ACCEDAF8BMC/7/+eCaA55SzSzRxFsb/Vw58dJsuaeT1n7ALNotqjO0E9Z/ozDS/dGHLZaZi2F2mVKWvGBgJM23Os5pEyBprC13O2CswZkzUtN2BC6hwIKMKc8e5sNyMS085ap1Bxdn0zWpwtjzkTadQH8pmLJLBzMY/xotTrN/vQMzupN5bqrDSSHOYlIZ8zxpwBwL2jaaE+pS8/PMPf+hefw/ue3sJPfftL3P9ukzP8XCRXE8gO2PamNasrzthGWbfdQBFIev5+J0x50XM2B1kJB0DUSiM5vgkoz5wRkmxAy7C73gGlwGtPJoEywwPe89O03cK2RNt9dTWYM0rpKaX0dUrpxymlb0T+5BZmBfBD8ApBAHgWXnbn/0wI+SNCyC8SQgY1vGZhZJk5isCTBZIjUFgDfxr6HLJmtFfLKBiN89LNDbx6MM5lrdjjWT5nmizDcWnAskwzFos4BpFFKgsr0XPGxuh95gwQm6IVRdBPIsKcTfiYszD83HvuoDgTuJHdjPSoLM1KQyGw3eXImkA+c/ZnR1M8OjPwwRRJkz1XHQkBQGhYzYOJ7014iyMjOA2nUws/+k8+i/Wugp/7xHuFrlnWc5bHchxOGHMmOK0ZKwIsx4VuuZXKmp2IlQZrBUhq7xBhznisNAhJ/v4Zu16WObu61slMO2EpAabtcnucAd75yaOcWCU251sDDaczK7g/nTfO/S5GCPkGeMXZ3/Z/pAB4L4Cfo5S+B559x99J+ecghPwIIeQzhJDPHBwsJ4+9Kllzf6uPiekk7gDzes5Y5ErWQMBcz1kOE5eGr7m+DpcCX308zvy9R2eetLGbMXnJdous12disl4LDuYsEuKeBWbe22REmTPbl6nqlDWLM2c8siZ7bu9GWKznbPmypiKJB5LnNWQngd0okoxNo/i032+WV5yV8TkLpzVTrDQ4mbORYWOtowZ2QKITm45L8RP//I9w/2SGn/sb78WuIOu22WPMWTbLcTQx0dfkzAnyKNjvTWMFTtWh50DUSv9CjnAAACAASURBVMPJ3ND0NTkyEOAXZykbmF5O0/zEcDDQlERmdqDJkEg55uzBqZ4paQKYY1h50gEYvCxSjoSAEptzxrDy5rbWjXO9ixFC3gXgFwH8FUrpof/jNwG8SSn9ff/vvwyvWEsEpfQXKKXvp5S+/+rVq/UesI+qZE1mp/HWyeLO07DyT7L3PLWFd95ctOFgYBfxlE1rFmAlntr2SMs8P6N7R94CndYvA4RNmuwGw0bEuZgzTeE2oW2yAS0wv2u2fPamTuaMFWcizNnJzOLa2QbM2STGnInImpGes7JsNC+0IrKm5UCRiNBkLTvn8xivT989wlZfxduurqU/l2AUVByhFUOyCa3puFysgWcyLKOryriy1hH2Ovul/+8ufvuVA/z0d7yE9z2dXoymYb2rQCL5subhmN+AFgiVhllsE8iumzqsNAzLDda1pGsmuinVM6xQvJ9nFzAzy04tVAkhWOsoQmtEHEcTE1dyPOVYSgDAF3rO0Nf4zs8ybS1bKVnB54Vzu4v5qQO/AuAHKKVfYT+nlD4EcI8Q8rz/o28E8MVzOMRUVGFCC4Qjx/cTijOeIuN/+9EP469/KL2JVpKI56xseD5nRViJ/W2/ryRnd8x2z2w3nYROPLJEpDjryJzZmtnmvU1ANLqFMWd1JgRoioSeKnMzZ4btYGo6XDvbzUBi8hY0kYKbITp6vyzmTFWKJAS4wq0BwUBAXnH2+hHef3s7czq2fM9ZlqzJpHa+4ox9v7e2e3jzRIw5+/27R3j77ho+8aGnhf4dgyR5Hlkns5yBAIHoJiAqa85/BoxN4jVM5UHUSiNrHRxoSqTnLF/WzCpgPOYs/fz18jWLM2dJRrpxXFnrgBF3QgMBGTYnUZgllBNWyDel76y2lZAQ8s8AfAretOebhJAfIoT8GCHkx/xf+XsAdgD8LCHkjwkhn4n88/8EwP9KCPkcgHcD+K/rOs4iMCxPuy/LdjDGgNkIzL9Gds8ZL/qaEpE1xZ9v2FWx0VMDZiwNbx7P0FUlXMkYW48zZ2zRybPSYL/DI2uuVM+Z5QR9T3Wa0AIee8ZbnDFGgsd4mEmf7LlHhrgE1NcUbPVVELK8ZIci/VterqHY8cXP+SQ8OtPxxuE01UKDQZUl2C4tbF3BmLOkz7gbDA/lX2PRYPv9rb4wc3YwNjKbxnnAkxJwNOEPPQe8zFVNkTCNZThWHXoOpMiaCYVNvyMH614W8wkAPS0cMkhCntURy9csijHH5L0qS0HBLGSlkTGsEYXnclDsvtm04qy6sy0GSunHcx7/YQA/nPLYHwN4fx3HVQVY/1aRcd0odgYaNEVKZM6KWF8kwcsks31Zs9jz3dru5QYc3zueYn+rn/mZRC0kgChzxtlzxilrbir8C/J5IJE5q1HWBMSKM97oJsCbFpYlMsecKRIRPteub/Rg2G7pa4oXns+ZWJHzZGQI7fYBz5sMyJY1Wb/ZB27nF2cAYLkuOpL4DShr3WKGp7qZXbDajgvDdoOb8P5WD7/+Jw+CtAseHJzpeNvVK4JHP4/NvspVnL2wNxR63iSX/bM6irOI1yGTy5OumYGmcMc3RQcakgq9aY5J+LCrlhoImPjmxHnYXe/iiaCVRj/D5iSKMrJmUJw1JMKp2RRDQ1GUhYpDkgiub3RxP4k5q6ixnQXG5iUOZOHWVh9vcjBntzL6zYBQTmHySjCtycGceTtIfp+bJiOROav5mIWKsyCUOH9nS4gnMQXTmronbYgWWTc2e0uz0QA89kh0Kuv1wwluXxEbHGfnYtZAwB+8foS+JgeJHHnPVbTvzGttSG8mB/JvfnHD1FtbfdguxaOzxTUsCZRSHIyN3Mi2PGzmyJqUUhxOzEwmPwlJAduMTapyWlORJSgSgeHLmmnXTL8jB5vYvIGAKBuXhKnpoJ/BbK13xTN4GVhoOk87A+s7E2E1WeGZZ6dh2g46BdfSoEWjIcxZs+9iDUXeJKUIrm908SCROXMrYc4GHW8E2SjFnPVzncDvHU0z+82Axck1kf6kNU2Babu5UtRqyJoR5sxlPWf1MkbDnoLTGd/Cy6bgeKY1vd9TcToNZU2RYQCGj764i298YVf43xWFIti/5boUrx9O8axocaZ432tWQfXpu0d439NbuQU6a6MQHWRgyFq3wptf9jky8g1T1yPMGYDctgeGk6kFy6GZU9082OxrwSYiCWe6DdN2cxvU40iyoxjVUJwBYQP/OOOaia57uu1AyminySuwp6YdMKRJWO8qwfcrCnbe8Fz77LsvImvmF2cuVKXYWtpRZKx1FBxlnFfLRLPvYg0FzyQlL25s9BZ6zmzHhePSinrOvEZ6vUSxd2url+kEfjqzcKbbuLXNyZxZbCDAu9B4Lmi248vzOluJ4iyyww0HAuouzlTuSSzGgm0N+BbPrb42J2sWKc6+/4NP4R9978v5v1gRVEG3/funM5i2W4A5877rtJ6zk6mJVx6N8MEcSRPgk0izYFjpa0Bh5myb2Wnw9Z2xNaQ0c9bPZoIZk3dNsLctyY6CXTci3n086CgSdMvJvGaCdc83Eu+qciornebTxjAxnCBMPQllBgLYeZH1/AwffGYH7396S+j+1sthBRksh5ZSTrYG83F054lm38UaiqKeYUm4vtnFwzM9MCMFwsmuKl6D9ZyZtni2JsO+vwCn7Y5ZBFUec9aJTa5NTRsS4ZvQW/Mv+nHOzn4VEgKizBm70WYZN1aBDaHijL/nDJgPPx8bduU3sTogmq3Jgtlv74gyZ9kDAZ95/RiUZvubMQSGtgWLM91Ot9PhvfnF+0TZpG3eNDfD47OKirOehrFhpxaqD/0N7zXB10ljztY6CndPHS+izFla3+0gMqihW9lG4nkTjTMrO16PyZpJpuh5mAgwZ9/zvn388o9/ndDzh4bq9W7Ot/vNydds9l2soTAyFjlRXN/owXEpDkYhK2VkZOCJYqApwY2zDHMGpC/A7Oe3couzME8O8Bb6NFPEOKI5oVlYBRPaaHHGivJlDASMDHtuE5CGk6mJripx94B5k3O+CS1nVup5QxOUNV/3i7Nnr4oVZ4EUmfJan379CJos4eVb6X6FDKV7zjIi3Hhlo7gnV0eRcW3YEWDOvKKprKzJWN20oYCHPnMmOhXaS+g5G1Uc3cTQUSXfSsPBWopkypizieEzZxn3hDz2c+Kvt2kY9tSgd0wUQYsKR/9wEbBJVL6BgOL3Zi9fsy3OVhZV9YMB4c4zakTLerLKnGQMPU0OGhyLFpSMEUsbmX8zYM6yZc2459M0h2aPgt0M8vI18zJJmwBCvMksw3KCG23Vu/I4RIxoeUPPGbYik3Nj3Qr6kZoM0WzN155M0Ndk4aIijzn79N0jvHxrg6sQVnIKvTxkMf55khhDUp/ora0+d0pAVcxZmHqRfCN9zGRNwfSBfkIAfNW5mgxdRYYRyJrJ3z/7+cSwfSuXDOaMedUlfIeOS2HYbmZaQpl8TRHPyiLopRgEx1F2IGy7r+Fw3BZnK4usHagoWHTNg9Ow8GELeSXMWUcJms6LPl9XlXF1vZMqa947mmKgybkNngs9Z2a+aSFDn2NnTyldCVkT8D5TbyBgebImwBfhdDK1uIcBAK//Z2Y5fv9M8hh/06AKuu2//mSC2zsD4SnUYAgmoaCamjY+/9ZproUGA29OZxqy8nV5e86SPLn2t3rcXmcHIwM9VS59jsQzXeN4eKZjs68KTwD31CTmzK58GADw2jl0y8VYz+g584uSiWn7PYPFZE2eyfj1Ahm8DGEvYj0T133OzYNRUtZsmbMVh+FUY6UBRIxoT8KhgCC7syKfM4YyVgW3tnqpsuabxzPc2s72OANC5i5kzrJp9igGHMyZ7VJQujwj0zJgzcDLmtYUK85MbAq4obNC7mRqBbYATYcqEViuy91fc/fJBM8IDgMAESkyoaC6f6LDdime31sXei67qAltBnPW5zT5TCrObm338fBM57ImYTYaZf3s2EYwVdY8NXBtXdzothfxFWMY6XY9zJkqBwMBadfMIGjncPziOkPWzCjO2PfKw5wVMaINir/amLPk3NM4zJJOCtsDLYg7PG80/y7WQJSxpYhj2FUw0GTcP12UNaua1mQoc8y3ttOdwN88nuZKmkCERfBP/InhcO+0BsHUUvrCYQZycPNP64A5W0J8ExBGz/AUZ8dTk3tSEwhZjKOJuVIDAZSCqwfPclzcO54VK84y4puYJMcrIQcmtEUHAjLyddmwUP605uJNeH/L65tNSjqJ4/GZUbrfDMgPP390pgtPagK+CW2irFkHcyZ7PWdm1rSmL2uygYCMe0I3o8BmHpFZ6+0wkDXFmbMimboi8MyTkyXbKMoqJ8x7rQnsWfPvYg2EWcLQNQ5CCK5v9hKZsyqKjGhcR6nibCt5d0wpxZvHs9xJzejrR7M1eS9mtqiMM6w0Vqk4C5gzh5nQNok5E5M1mVktS7pI659pEkJbivzi7N7RFI5LhW00gEhBlcCcMZ8uXr+n8j5n6b2yku9Qn8+cOdBkae4aC3pSOfrOqjCgBYDNnIGAR2c69obir8Om26OM6ki3MezVwZxJOJ5YoDS9qGHMWTAQwMGcJbE+bFObFd/EpFtes+ooWNGeNQ1aBoSQRMk5DtN2S8UqRjea543m38UaiCqtNADfiDaROaui56wiWXM7eXd8OvOkLBHmLMjWNO3MxSKKAce0JmMnVqE4C3vOvJtA2ZzWPPAWZ5RSnMwsrnSA4Ln932VN4Wud6lmGqiFiS/H6oTepWYQ5UyQCQpJf52TGkhg4mTPOEPU05PXK9rVFG4k4Jgm2D2xKm2di8/GZXglztu5bWySlBNiOiydjA3uCwwCAJ5+5NPyMKaX+tGYNzJki44nv+5Yqa3b4rTRUP3UguefM9yHLKJ72t/qQCPDawYT7PTBMBHKSi6KvyZmypuNSuDT0FiyCgDlrgBFt8+9iDUSVCQGAZ0T71hxzVl1x1lOrYc7Cic353TGTOpkZZRYUiUAiUeaM33ahp8ogBJn5mgFztlI9Z94xyzXLmsG0Zo5kcaZ7dhti05re77Kb8yrImprA5CO7WRUpzggh0GQpsYmfSXIbnIVw+fimfJ8snmnN+DV7fbMLiSA34k23HJzpdiXMGSFkzl8vioOxAZcCu0WKs1jjuW65sBxam5UGWwtzBwIMJ3daE2DfYdLwCSvO0t9HT5Nxe2eALz884zr+KCaGl9sp1dg7203IPY2iCuVk22dkm5Cv2fy7WAPh7UCro2+vb3bxZGwEcmboc1b+NaK73DJS7K0U6YKxJTzMGSEEmiLNmdDyBOUCnuzSV7PzNY1VkjX9hdlaUkJAV5WhKVIucyYa3QSExdm9gDlbAVlToH/r7pMJNnqqEJsYhZZieHsytSBLhNt6pGzPWR7j381hJoDkeC5VlnB9o5fLnDEvx90CjfpJ2IjEhkXBDGiLMmdA2HvH+q/qmNaMru9pxZksEXRVyWfOsmVNwPsOE5kzTtnxhevreOXhKO/QFzARUEGKIin3NIoqirNgCriVNVcTVfqcAaGdxqNTw3/+enrOeJz408B2x/GhgHtBcZbPnAHegmRYDlyXYmqKGZYOOgoXc9Z0nzPAkzSi8U11W2kAfCkBQXSTQCHSVb0epIA5WyFZ0+ZgoVjgedEJQ01JZs6O/alY3ufNM7TNAqU0cyAA8D2+OJizpELiZsY0N0NV0U0MW30tUdZ85HupiRrQAouWPWxysa5pTYasdXCgKcFAQN6GPWmgAYgMBOQUUC/sDfHG0TRznU3C2HBq35T1NCVTdjec8vfNjZ4KQoDDtjhbPbiu56VVtawJIJjYrKvnrAwTx3bHi8zZDMOuEshmeWDM2cScj4HhwaCjZDJnq9RzxpgzJ5A162XOAG/hyWPOjgswZ4QQbPXVQPKuy+uoSrABDJ7+rbsHE+HA8yjSirOTmSUU/lzG58z2+3Gy1hSehus024f9rXzmrCoDWobNnprYG/SooAEtEBZMs6A4q485i26Wswaj+h0vHzkrG5UhTZpm5q1ZVhoA8MLeOigFvvJIjD2bLsFCp6dmD6wEm/MSG11FlrDRU1vmbBUR5l5WK2sCoRFtcJJV4XNWUc8Z4A0FxHvOeCc1o8dgWG5wExBjzmTOnrPmFwddRYZhhwkBdQ8EAN6ofF5xdlqAOfN+XwtZhhVgzjROiVC3HNw/1YUzNaPwQtaTe85EimBNYMI0DoNjTekm5ErGkTZhzaa5swpHxpxVMRAA+LJmwvn88EyHIhHsDPg/W4b+gqzpndP1TGtGZM0MZm6gKRjpFkwnPx85TdbksdIAPOYMgLC0uQx/w34Oc1bVtP72QGt7zlYRVeZeMgTMmT8UUKnPWUXTmgCLaYnJmkdT3NrO7zdj6CgSDMct5IvT1/hkzVVhznQrTAhQliRr8jJnIgMB7LkZVmEgILS4yC50gklNwUzNKKJ9llGcTMWmYsv0nDFvwVxZM3daM9mbcH+rB0pDO5UkHIwMEBJOxJXFVj/Zzf3RqTcRWqQ5PW7Gy3rO6pnWDK/5rKJp0FECa4f8gQApc1ozr7jb3+phoMn4smBxNhHoHy4Kj9mtf1p/u6+1zNkqokr3foaeH330IJA12UJaTfA5Q3nmrI/HIyNYwEU8zhg0RfaYMyN/eiiOtY4SyKFJMCvoOVgWWO/dshICAN7izAIhoWktL6LF3CrImry2FCzw/JmSzJmZUASeTC1s9PgLlTI9Z2zDl+eTVVTWZNPaWdLmwUjHzqBT2UZks6diajrBesnwaFTMgBYIi5+g52y2nJ6zLLa5r8mR4ixf1kz0OeOcppQkguf31vGlB2ITm1OByfui6GnZ08RVTetvDbTW52wVUSWrFcX1jV7InFnVWUJ0Vc9ZGShfnLGJTLYAH05MzCwHtzgmNRk6igTDdiJBufyfY1+Tg6IuCStlpaFK0OcSApZTnLGbTRpOpiaGXVW4B44lCmiyVPm1UQd4C53X/OLs9hX+DUgc6cyZWaznrERxlvXd5DVcU0pT3ezZ2pA1FHAwqsaAlmHTZ+DiG46Hp3qhSU0g3CzOLO86qXNakxVnEskuugaaEjSo5zJnKQXM1HK4DWKf3xvilUcj7mgzQMxQvCh6ObI7u5bVKpizVtZcPVTJakVxc7MbSAKm40KTpUo8YwjxLCgUiZTesbLdMVuAWZEmxpx5zdE8QbxxrHWUzGzNVbLS6CoyTNsNFpRlDQSc6RbcjMiiY0GpjYH1Tq0CawZEcipz+rdefzLBlbVOKVmrI0swY+yOabuYmE4xWTNHik2CbuWvW70cH6mp6aS62e8Nu1AkEljrJOHxqJroJgaW/xpPCXh0ZhQaBgCiPmfedTnSbcgSqcX5nn0Xg46SObHb78hB71uulUZKAeMxZ3xr7YvX13EytYKpVx5MBJ6/KPKsNIwKmTMvuaGYn2BVaP5drGHQa+g5AzzmjLnv5zl5i6LfUSp5vsAJ3B8KYMMBPAa0DB5z5kaYM7GeMx6fm1Ww0mCy+MRwoMqkdBA0D4Y9FZR6XlVpEG1SZ2A3ylXoNwPCHr885uzuk3KTmgCgKmShiZ9ZQGwIfNayRCBLpJSsmdWO0dMkTC0n9aaUlKvJoMgSbmz28PrhEpmzhPDzsWFjbNjFi7PASsN7r2e6hbWc4qkoGAuW53MXLYbzesZSZU2TnzljQwFf4jSjdV2KibkMKw0vVSVtc1ndQIDqOwqcb/h58+9iDUO4yFUsa252cTqzMDVtGLZTKfvT1+RKjnd3vQNNkXDPZ8wYc3ZTUNY0bTeI+xChwtc6Miax3LsoVslKgy2yE8NeCmsGhH1kWV5nx1OzEHPGes7qjG+pEiqnlcbdJ9NSkiaAxISAk4JTsapcsDjjGghQ4Lg0dRo0b4jnuWtr+NMUCwbXpTiomDkLDEMjEhSz0djbKPY68XzKunI1gbBQztugzntV8iQElCvOnr+2DoB/YpMxdfVbacxP0sZR1eY8yNccn6+02fy7WMNQl6wZndisOruzr1XDnEkSwf5maKfx5vEUW31VqMDq+BYSQRCvSM9ZRwGl+RfnqvScAcDYtKHWHN3EwJOveTyxhCc1gZDFqKNxug7wWGmMdAtPxgaeubJW7rUSfM5YcbYpMBAAAKqU3L+WB56BgLjHVxxBfmLK9f72a+t47WCS6ulmu7RS5iw4nyPM2aPT4h5ngPddKRIJGPqRbtVmDcM+77yiJjoFmTeIdnOrh4np4NWD8dzPJya/1cVGX8WNjS6+zDkUkMWoVom4zUkclU1r+r2M522n0fy7WMNQV1/T9Y3Q68y03UqZuYEml7bRYNjfDu007h3PhCRNIGyODmRNAaaFXfxpfWcrZaURYc6UJXicAXzFWWFZ0/83dTcFVwUeW4rXn3ibkGdKMmdJPmeh2a8gc6ZIXKkGcXANBOQwEyPDO2/S+gqfv7YO26WB/UgUj0de0VRVdBPg9QYB88zZw7Pi0U0M0cbzs5ld24aDsed5z9/v8DNnf/md1yER4Ff/6K25n89MJ/h+efDC9SG3nUaR4a4iyNs8VDmtCZx/hFPz72INQx0+Z0AY4XT/ZFZ5sHpPkyt7vluRmJY3j6dcmZpRRE1ou6okJOmxHWTaxOYqFWfdoOfMrj30nCGvOCvSpM7A/k3du+eqwCa6sprrX3visQ9VMGdGjE1ibI9wcVZQ1uQZCMhjJvJaEd5+zfucktzlWa5mlczZQPMGnU4i5/PDEukADNGJxzPdEraV4QVbA/I2qNFerryes91hF3/ubVfwL//4rbn2DxHmDPCSAr76eMyVRhEYitc+EKDMvV4cVa3/zLz4vO00mn8XaxhCWbPaXcK1YReE1CNrfvyDT+EHv+52Jc+1v9XHydTCmW7hzeNZMCTAi06EORNlWfKYM8N2QchybCnKgp0/I91eSjoAEBZnaT1nrEl9s4BJKGPOVkXW5Ok5Y8zZ0zvle87SmDNRCVlNCVHPAw9zFnp8JV9fk5yesztX1yAR4CsJjEsdxRkhBJt9bW4g4NGpjvWOUmqT0I+47I/0Gpkz//POG6IRzUf+rvfcxL2jGT77xnHws5np5EY3RfH8nseCsg1KFooYihdBT/Pee92yZhIjex5oizNBVJl7GYWmSLi61sGD0xkMy62U/fnWd17Hxz/4VCXPxdIA/vCNY5i2K8ycaYw5KzB6PcjbOfkWJMuYfCyLgDkzmyNrhn1Q4kwBe+5VGQgIrTTSC527T8a4udkr3RKQ5HN2MrOgyuIWDV6hV0TWzDfPZseSlhKQdxPuqjJu7wzwlUeLN/THo2qjmxg2+ypO5gYCjMIGtAzdiBnvmW7V4nHGXgfIL2oGgikvH3tpDz1Vxr+MSJsTwxFy8H/xujex+eUH+dImK9r7tQ8EsPU/u61FLSlrrncUKBJpmbNVA89IelFc3/TsNLxg9Wb6RTGm7FOvHQLwetBEwAYCxgUcpdkilRbhZNrVFrV1Iuw5c6AsSdbs+zJQWnHGeiyKDARoioS/+dG349tevlHqGJeF0EojvdC5e1h+UhNIm9b0evtENxKqLMEqEHzO047BGKK084On8fvt19bwlcfJzFlfkyuXvTd76hxz9vCsuAEtA4uxcl2KsWFjWBtzxqY1s9d6kWlN7/kU/KWXruHXPvcApm89MbMc9AQ2Ts9cGUCTJS47jbBor99KA0jfPIS51+XWU0KI53XWMmerBZ6R9KK4sdGtpeesSrABgN971SvORNIBAO8m7lJPWhO9mNnCnhbhVLUcXCfYwjw27KXJsIQQDDMinI4L9kEx/M2PPod339osfHzLRJ6sSSnF3YMxninpcQZ4/W1xWfNkahViKD3PtDLTmunX3K5f1DxOMR+dGDYIQSbb9/y1dbz+ZLJwA63agJZhM+bm/uhMx+6w3Ov0fLNTz7annlxNwOsf+9Az23jvU1uZvzcQlDUB4DvfcxOnMwu//crj0OpCgDlTZQl3dte47DSCnrMlTWvm9pxVMK2/3T//CKfVuJM1CFVV50lgRrS65dbCzFWBrb6KgSbjT946BQDc3BTvOQO8MWVhWZMVZ1nM2QrYaABhcW/a7lJCzxmy8jVZtmuZZupVAbMvSSt0jqcWznQbt0tkajIwKTJqnun5yYkzlEV7zlixlHV9XF3zihomQcYxMmwMtGxD1rdfW4dLgdcO5ic2D0Z6pf1mDJv98Hx2XIrHI6M0c9ZTFcxMB2d6fbmagGdN9M9/9MP4xhevZf7eQGAggOEvvO0KdgYa/tUfvxUUM6IS+ot760Ky5tJ8zjKKM0UilSTrbA3UtjhbNdQ1rQkANza7mJoOHp/pjS0yCCG4td2HS4Erax2hJlMgbNY8npjiAwFaKAUmwXSqtSCpE9Ed8LIGAgBkMmdvHE6x1lFwZU28aFg1SBKBkuG2f9dvhH72agXFWULI+snUwkYBhjLJloMHhp0fCacpErb6amB7EYcXep59fT3nG5jGJzY95qz6on+rH8qahxMDjkuxV7LnrOcPBAS5mjVNa/KCFT0ikX6KLOHbX76B//tLj/HQ934T3Qy/cH0dD8/0uZ6+JDBZs1/z2tvL8zmrsK1luwHh582sABoMwz8B6mg6v+4b0Z7pdmN7zoAwS1N0GAAIGaPjqSm8k2OLSzpz5jS2qI0j+v0uKyEAYOHnacXZBE/v9FdioKIKqBnN9Xf9Sc2qmDNgnqU7nRXLMC0zEMCzodxd76ZmKk4MJ3dD9cyVARSJLBRnVUc3MWz2NcwsB7rl4NGpd9xlmd++KmNq2kGe5XlPILN1UlRN+a733IRpu/jf//DNuefhxfN+jFOe3xmzRapbAQisXrIGwioqzrb6WtDmcV5YjTtZg1BnP9j1zXBRaaqsCYRFmagBLRAyji4Vp8E1RYImS6mZZ6s0EDDHnC1pIADIljXfOJxWUoysCrI8w+4+GUOWSKFzPI6AOYs08h8XNPstHN9k87VKlQPufgAAIABJREFU7A47qbImj/2Npkh45sr8xKZuORjpdi3FWXQCuQqPMyD0OWObmLp6znjBNqWiU8Pv2t/As1cGYXEmuN6+uOexoHlJAUVskYqASbpZPWdVbc5v7wywN+yea/j5atzJGgSv6bweVuvmZshENbmxnd2wijBn0eKpiKP0oCOnM2cV7pzqRvQcWpaVBgBs9JSglyYK23Fx73iKp0p6eq0SsiTC159McWurV3osn70OEE6G6pYD3XKDwkL0uXiMQeMwLL516+p6BwdnWbJm/k34ub31OeasDo8zhmi+ZhXpAEBU1vSuk7qmNXkhSwRdVeIeBmAghOC73nMzeB8iAwGA931tD7Rc5mxSwBapCCT/c1iGrPkffeRZ/F8/8RfOVUVYjTtZg+AtcvV8bFfWOsHkXpOLDDahKWpAC8wXnUUaSPuakjqtuVoDAeFxLlvWPJ1ZCzvCB6c6LIfi9mUrzlISAh6d6UGbQVnEmbMw9LwAc5Yw+ckD3Xb4mLP1Lg7GRiJjMOYtznbXce94GvhRPa6xOGOTxSdTC4/PdEgEpXsm+6oMy6FBz9F5M2eA54XGOwwQxV95983g/0X7gwkheP7aOldxtqxkkLRgdyD0ubwouDjvZEkwOBe5IpAlElDyTe45e9f+Jq5vdPHep8VtE6JFZxEqfK2jXAifM0kiwUJSBTvDi2FXhePSBWmY5SE+fZlkzQxbiiqd4cOBAO8zD5IYltlzxsmc7a53YDk0sd+GV7567toaKAW++tiTNg+CXM16i7OHp95EaNneJ1bEsKLyvHvOAG9TWsQM+amdPt7/tGfVUcQg+oXr63jl4Whu0jgOrxdxOfervqZky5orsv7z4OK8kyWhTlkT8CY2gWbLmnsbXXzqJ78RL/gNoyKIfnZFqPBBR069OI0VuzjZd7zMuKm0lIDXD6trgF8VZNlSjHSrMsZEY55qPkt3PCnuJ1e854xzIGDI7DQWpU2eaU3AkzUBBH1ndcqarG/vxJc1y0qaQKQ4O9OhKVLphIgq0NdkYVmT4a9/6Cn0VBnbBRjFF/eGmFkO/uxomvo7ormdZdDzDYKTsEptLTy4OO9kSajb6JRJKU0uzspgnjkr0nOmpGZrrtrFyWw/lttz5hdnMWbkjScTdFWpFnajqUjKvGQYGXUwZ95rnTLmrFfM56zwQADntCaQbETrMST5BeXT231osoQ/9fvOHo8MSATYGdTRc+YzZzPLN6CtoDjzr8tHI/3c+80Ybu8MCrWRAMB3v3cff/h3v6lQDNUL1/2hgAxpc+z73y0DPX+SNgmr1NbCg2aceSsEw6rXvZ9NbGoNljXLIPrZFWLONCXVwdy0XXRW6OIMmbPlTmsCyczZ09uDSgwcVwWqLMFOkAhZbE9VxRmTrVnPGZMMtwZLHAiw+QYQWHEen9g0bRem43JtqBTmLu8XZwcjAztrnVp6K3uqDE2WcDw18ejMwIee2Sn9nMyy4dGZ0Yh+MwD4mY+/B2V600X7zRjevusVZ199PAKwl/g7vIxqFWDDGkloZc1LDm8kvUZZ84IzZ6UHAjpyOnO2YhcnkymWyZwNU4oz5nF2maDKJFHWDGN7KmLOYj5nYcB8USuN7J6zpGZ+w3LQLSFrirrAP3dtDX/qy5p1RTcBXtP6Rl/Fo1MdpzOrtAEtEFpWPD5rDnOmKdJSe1MZepqM9Y6CJ+N0Q9ZpgZzkwseTNxCwQut/Hi7OO1kS6pY1b/h2Gk32OSuDaM9Z0YGAVFp7xS5O9lmcR8/ZmR4WZ65L8cbRFLcryJFcJSgpEmFoPlpRz9nCtKaJjiIVYjNUWYLtpjNnP/P//Cm+9+c/tfBz3k1lX1Ow3llkp8fCxdk63jqZYaRbtRnQMmz11UB2qyJ6jDH6Z7rdGObsPLGzpuEwxS2fUur1nC1J1uxr6T3HF03WvDjvZEmoO5T8uWtrkCVS2Rh/0xAtOkUdq71/o6THN63YxRkyZ0uUNf0enWhKwMMzHabtXjrmLG3ykRUiVRlrBrJmhDkrGi7PUg3SzDFfeTTCZ944DiJ7GETaMa4OO0ETP4PoZ8JinP708RiPR3qtvYybPQ2vHngs3bWSoedA2HMGNGNS87yxs9bB0SS5lWRmOYUMxYuip7ayZosU8I6kF8XTOwP84X/xTXifP/580RAtnooxZzJMx03su1m1i5OdR+oSmbM1TQEh87Ims9G4TJOaQPrkI8tUrOrG3FHiPWfFQs+BkIVLkzaZ5POp157M/VyE8d9d71QiawLAKw9HeDI2a2XONvtq8HlUOa0JoFAT/UXD9kDDYYqsyTbKy7LSYOkNSWh9zi45lmHXUCQQeVUwx5wVuKA3Io7gUbguhe3SlSrOGHMmL3EgQJIIht35CKc3fBuNy8acpTXXn9Uta86sQukAgFdQAkid2GSS/ye/ejj3cxELoN317sJAgChzdmurj64q4fdfO4Tj0lpCzxmiLOS1CnrOosVZy5x5pr5psqZo0V4W/XYgoEUa6pY1LzpC41VSiIFkO+O4bMMko1W6OAPmbIkDAcBivuYbh1NosnRhpfQ0pLntjyuO7VEXBgKKM2fx54ojZM7ixZnD7ZO1u97B47P5lICQIeH7TCSJ4O276/i3r3rHUS9z5n2Wfb95vSz6c7Lmxd0o82J7oOFoYiYa0bKifRnxTUAoaybJ+qvWc5yHi/NOlgTeAOEWyVBkCbJECl/MQXEWy/8zfFZilWjtzjlMawJJxdkEt7Z7S42RagI0WYKdcMNhAwFrNfmcle05iz5XHKxZ+s3jGe75xqGOS2E5lJ85G3Yws5y5qeix4Z0vIpYJz11br9WAloF9lteG3UqyEOdkzV7LnO0MOnBcujDhDYTM2TKCzwGgpymgNFzvo1i1nuM8XJx3sgRQSj0vrQvqQbYsaLJU+GK+tuEt8o9ixRmTjFaJ1ewG05rLPeZ4cfb64fTS9ZsB3pSslbDIhz1n1bAmUZ8zSqlfnBXsOZOze86mpoN33PSSOxh7Zthewca7qQyMaCPS5liQOQPCvjPvOesdCACqGQYAvDWE1Xgtc+ZNawJIlDbZZmBpPmf+OZw0sdnKmpcYxgoWAE1ER5UKX8xXBl44/IWQNRlztmTGaqOnBtOalFK8cTjBU5es3wzwZE0zocgZ6TYIAQYFjTvj6ESYs5nlwHTc4syZ4vecpRjRziwH79rfxM5Aw+/5kqJhia1bgRFtxE6jSG8Rm9gE6mXOWEpAFcMAgOedxqTNtucsTHY4HC9ObIparJQFU1zifWer2HOch4vzTpaAtjirBh1FKixrShLB7npnQdZkzNkqXZzdIL5pucc87Ck4nXmL6sHYwNR0LiVzlhbfxAK+q5DIgHnm7DgwoC0na2YNBAw0GV/77A4+9dohKKWRdYtf1gTmjWgnhi1shMoyNtc6Sq09SWyAqophAAYmbbbTmiFzdpTAnC17IKDrfy+zmNflKm7O83Bx3skSEMoDraxZBppSXNYEvEU4bpIZFGfy6nw3rMhf9kDA0GfOPNbsck5qAulWGme6VelNWZYIZMl7rRN/yriorJnVc+a6FLrloqcp+No7O3hwquONw2m4bvH6nCXka44NW7jZ/sZGF2sdpVbWDEAwXHGtwolQVpy1zBmwM/A+3ydJxZkvL64ty4TWv/fGZc1V7DnOw8V5J0vAKvY1NREDTSlsJQB4i/BFYs6W3Yi/0VNhOi50y8XrTy6nxxmQHiI+0qvL1WTQfNuOILqpoKyZ1XPGpJ6+JuPr7ngZk5967RC6L2t2OTeVw66CjiItMGei7AghBF9zY4j9rXqngJ+5MsBHX9zFR567WtlzMiPaljkDtvzi7CjB64wxZ0VskYqgHzBn88XZKq7/eWi3BQJoZc1q8N9978ulmLO9jS7+7VfnTTZNx7tYV+niDILPl7zbi4afv3E4hSwR3Kz5BtpERN32oxLmWLcrnz7TlPnirA4rDcYm9DUZz14ZYHe9g0+9eoiXbngDArzrFiEEu8NObCBAvDgDgJ/5/vcI/xtRdFUZv/iDH6j0OXs+E9ROa3rn3EZPxWFCSkARubsMmKw5jfWcseuhZc4uKcLG2tWRzpqId9zcKJXjeG3Yxciwg10bsJq0NpPHl5kQAMwXZ68fTrC/1TuXUOXzBivk43YaI8OqnDlTZW/44DiQNUua0CYMBDA2oafKIITgw3d28MlXQ+ZMxAJod727IGsWcYHf2+hWEka+bLCpwGVZRDQdO2vJKQGsP3NZuEzM2cV5J0uA6Eh6i3qw59tpRKXNVbw4GZNxHrImEDJnT19CSRMIp2TjLNSohsDrjs+cMQuTwgkBSnrP2dSaNwT98LM7eDI28MX7p/4x8BdX8QinieEsrem7CehrCvqavHRWu6nYGWiJzNnUdJZmowGENi/3T2ZzP28HAi45WlmzGbjmj8w/Ol0szlbpu2E9QMtmreLM2e1LOAwARCRCe545G9fQc6bKBKbj4nhioqfK3P1fcWT1nEVlTQD4sN939ttfOQAgdm14xdm8lcZlKs56mtz2m0WwM+ikMmeDJQ0DAF5awVZfxasHk7mfmyuonOTh8lxtFUB0JL1FPWB+Ro8iO/tV3DmFPWdLntb0bzpvHE4w0u1Ly5ylsVAj3a4sHYBBUyRYtouTmRX4chWBkpGtGciafnH21HYfNza6+JTvdyZSEO4OuxjpNnTLQVeVC01rrjK+89038fL+xnkfRmOws6bhD15PHghYdtF+5+oaXj0Yz/3MWEHlJA8X550sAYYlNpLeoh5cC/I1w539Ku6cguLsnGTNz73pyV2XlTnTEgod3TeJrZo10RQJpuMNBGwUHAYA+AcCAK+x/2vv7BRi/ONGtJeNOfumr7mGH/nInfM+jMZgZ6DhaGrCifVnTszly913rq7htVhxtoptLXm4OO9kCWCLHG+AcIt6MOgoWO8ocxFOq3hxBia0S45vGgbF2QkAXF7mzC907IhEyHI16xgIYD5nZZizbFmT9ZyFDNnX3bkS/L/QQMCQRTjpcF16LjfhFs3BzloHlCLw6WOYGHZlSRq8ePbqAE/GJk6nYQQdY78vEnFycd7JEtDKms3BtY3uXITTKtLa+1s9aIqEW9vLZa5kiWC9o+D1wykIAW5tXz4bDSDZ0HVcU5CzJkswfFmz6KQmkM2chbJmeOys7wwQHwgAvHzNick+k3bdu6zYHiTna56XrAkArz4J2bNVNCHPw+rcyRoAUaftFvVhb9hd+WnN/a0+vvJffQue31vP/+WKwdizGxu9S7vZUBNkzapDzxlCnzOzcDoAkHzMDIGsGektu7nZw1N+8V9M1tQxMVi4dcucXVYE4eexoYBlW2kAwJ1dvzh7HBZn7Hpg2bMXAatzJ2sAWp+z5uDasDsva15AE8I6wfrOLmNsE0MSC1WXrBlNCCiaqwlEhhiSfM6s+YEAhg8/67FnIsXZVl+DIhE8Hhm1sYktVgdX1vzw84idBqV06VYaAHBrqwdVJnMTm6vYc5yH9moTQCBrtj1n5469DW/U33EpZImspAnteSIszi5nvxmw5OJMkXAyNWG7tJSsmddzJpHFIuzH/+IdvPupTSHPLkkiuOrbaUza4uzSI5A1I8yZYbtwXFprqH0SFFnC0zuDuaGAVVRO8tBebQJgsmZbAJw/rg27cFyKw4mB3fUuTNuFJkuQljz5uKpgsTSXdVITiPSc2dGBAF/W7FQra6qyFPiGlZM1s6c1+5oyF0UFALevDAolcjCvM8actbLm5cVWXwMh8z1n58mo3rk6wFcjsqaxglZKebg472QJMNoCoDEIjWi9G55puxfqwqwbLXMGaEpSz1l9zBmLiSoja8oSgUTSBwLikmYZXF3v4vGZ3sqaLSBLBFt9DYfjUNacnmMv4p2ra3jjcBpcB4EJeTsQcDlhWG0B0BQwI1o2FGA6TvvdCIAVZ7evtMyZ7SZMa9ZQnDFsDYozZwDL6Uxjzqq7Oe0OOziIyJotc3a5sTPQcJTAnC3bSgPwijPbpfizoymAiylrXpx3sgQYttNOajYELEw5KM58VrMFH25u9tBTZTy9fXmZszRZs6tKlUdqRc/NMswZe6545BTgFWe9grFQSdhd7+BwYuLE95NaduN3i2ZhezAffs4sVs6jaH/2qrduveYPBbTF2SWHYbttcdYQXFnrQJZIkK/Zyppi+PiHnsJv/qcfqVQGWzUkW2lUH3oOzN80yvScAd7EZqKsadnVMmd+yDRjJ1pZ83LjylpnblrzPHsRn2VeZ/5QgOk4kCUC+QK1HLV3MwEYtotOhTvTFsUhSwRX1zoRWbMtzkTQUWTsb11eSRNIn9asut8MmGfONkoyZ6pMMgcCqgLzOnv1YAyJoFJWrsXqYWdNmxsIYD1n51G0b/RUXF3vBF5nlkODzdZFQXs3E4BhtbJmk3Bt2Am8zlpZs4UoEoszox7mjL3WWkcpvYlI6zmreiBgd+gVZ68dTDDoLE6Btrhc2B5oOJlawfXCehGrZGtFcOfqIGTOLuD6f7HeTc1oZc1mIWpEa7SyZgtBhPFN8z1n6zUwAezcLMuaAX7PWaLPWcUDAb6sef901kqaLbDjG9Ee+/ma5z3F++zVNbx6MAGl1F//Lxaz297NBOANBFysE2CVsRfJ12x7zlqIgu207SXImkxy2RqUL85UWYKVkBBQdXF2Zc3ztqK0ndRs4U1rAqER7fQcBwIAb2LzdGbhaGLCvIDEycV6NzXD6zlrP7Km4NqwizPdxsx0YDoX7+JsUS/UBJ+zcU3FGTs3N3vlhgEA77iTfc5s9NTqjl2RJewMPLakLc5asOKM2WmMDQeqTM5tU3zHn9h89WByIXuOL9a7qRkXsTpfZUS9zi5iz0GLeqFIi1FII93CWsXpAEAoa5aJbmJQJAmWOy9rUkoxtaplzoBwKGCttdG49GCy5hPfiHZi2OdatN+JTGyatnPh1v92OySAv/re/Up6RlpUg8Dr7FRvZc0WwmBSI/NIclyKienUJGtWV5xpCbKmYbugdDH0vCx2hx188UFro9FikTmbGDYGS87VjOLmZg8dRcJrB+MLuf63V5wA/sM//8x5H0KLCIIIpzP9QtLaLeoFIWTOloI1ONdipeGfm1slPc4AT9Y0rPnibGp6tgZ1MWetrNlio6dClkjQczYx7XMt2iWJ4Jkrg1bWbNGiabjmj/o/amXNFgWhyqGhKws9H9ZopVEF8x49ZgbWnF19ceZtgFrmrIXE8jUnTNZ00D9nufvO7hpePRjDslufsxYtGoP1roqBJoc9Zxds59SifqgRWwoWel51riYQ7TmrgDmTpTn7D8DzOAOAXsUyE/M6a5mzFoA3wcuYs7FxvswZ4PWd3TuaYmTYrZVGixZNwrWNbsictcVZC0HMM2f1yZodmcmaVfmcpciaFbv4hwMBbXHWws/XbEjPGeBNbLrUGwq4aMpJbe+GEPJLhJDHhJDPpzz+CULI5/w/nySEvBx7XCaE/BEh5NfqOsYWq4+9oed1ZlzAnoMW9UOb6znzZM06EgLesb+B737PTbz/6e3Sz5UU31RXz9lVX9YcXOIM1hYhdtY6wUDA1GyArOlPbF5EJ4U6380/BvDNGY/fBfD1lNJ3AfgHAH4h9vhPAPhSPYfW4qJgb9jFozPDuzgv2M6pRf1QkmTNGliiYVfFf//X3o2NCpizJBPameUde9XTmk/v9KEpEp7audw5rC087Ay0wEqjCbLmM1cGwf9ftM15be+GUvq7AI4yHv8kpfTY/+vvAdhnjxFC9gH8ZQC/WNfxtbgYuLbRxYPTGYCLd3G2qB+qTIKcyjO/OBvWIGtWCVVZ7DkLmbNqj/3KWgd/8J9/FN/w/G6lz9tiNbEz0DDSbZi2e+4+Z4DXC3ndt1RqZc168EMAfj3y9/8BwH8GYNEGOwZCyI8QQj5DCPnMwcFBXcfXoqG4tt4B8+Nsi7MWooiyUOOg56zZXoaZPWc1yI8bfbUNPW8BIDSifXiqw3bpuTNnQChtXrT1/9zfDSHkG+AVZ3/b//u3AXhMKf0sz7+nlP4CpfT9lNL3X716tcYjbdFEMCNa4OLtnFrUD02Zt9KQJYJuwyPaknrOwmnNtjesRX3Y9o1o/+xoCqCezYAoWIzTRSvOzrXsJYS8C550+S2U0kP/x38OwHcQQr4VQBfAkBDyv1BK/8Z5HWeL5oIZ0QK4cKPULeqHKkuw3bDnbL2rNJ4lSvY5q485a9GC4cqaV5y9cTQB0AyLlTu7HnOmXrDN+bm9G0LIUwB+BcAPUEq/wn5OKf1JSuk+pfQ2gO8H8FttYdYiDXPM2QXbObWoH6pMgvimkW7VYqNRNZg3G6Vh39nMN6HtthuUFjUizpw1QdZ89srFlDVr+2QJIf8MwF8EcIUQ8iaAnwKgAgCl9OcB/D0AOwB+1t+p2pTS99d1PC0uJq6udSARwKUX7+JsUT9UWcLEj20aGzbWawg9rxrsPLccCk3xWL6p6aCnypCkZrN+LVYbrOfsXpNkzV1P1rxoVhq1FWeU0o/nPP7DAH4453d+G8BvV3dULS4aFFnClbUOHo+MtueshTCiCQFnul1LOkDVYDE1VsTbb2o5jbhRtrjYGHYVqDJpFHO2N+ziJ7/lBXzspb3zPpRK0d7NWqw8WN/ZRds5tagf0eb6kW433kYDCHtron1nM9NphwFa1A5CCLYHGt449IqzJvScEULwo19/B7cjnmcXAe3drMXKgxVnrazZQhReTmWYENB0Gw3AY4sBBIwf4AWft8xZi2VgZ9Cp1bC5hYf2btZi5bG34fVBtMVZC1FosgQ7khCwCjcbLSJrMkxNp/LQ8xYtkrDjT2wCzeg5u6ho72YtVh57w4vpEN2ifjBbCkppYKXRdKTJmlWHnrdokYSdQVicNUHWvKho72YtVh57Gz0AQKfh5qEtmgfF7znTLReOS1dC1kwqzqZmOxDQYjlgE5uKRNo+3xrRlr0tVh4fe+kanoxfwHO76+d9KC1WDKoswbRdjHQLAFaKOTPtiM+Z1Q4EtFgOmNdZX5Mbb9i8ymj+StSiRQ7Wuyp+7OvvnPdhtFhBePFNNAg9X4XijHmbzTNn7UBAi+WApQSsQn/mKqPlJFu0aHFpwaw0VpE5W5Q1m3/sLVYf2wNP1mz7zepFW5y1aNHi0oJla44C5mx1es7M1uesxTmATWu2xVm9aIuzFi1aXFqwQud4agJYDalGjfmcmbYL26XttGaLpYBNaw467flWJ9rirEWLFpcWzH7lcOwVZ6sga7JjtvzA9pnpAEDLnLVYCti05qCV0WtFW5y1aNHi0kLxDV0Zc7YSsmZsIGBqeZJs23PWYhkYaDI6irQSLPMqoy3OWrRocWnBJMLDyerJmqznbOozZ+20ZotlgBCCb3xxF++7vXXeh3Kh0fyVqEWLFi1qApMIj8YmBpoMWWq+b5MW6zlrZc0Wy8bPfuJ9530IFx4tc9aiRYtLCyYRHk3NlZA0gUUrjZY5a9Hi4qEtzlq0aHFpEUxrTsyVGAYAPG82IFqcsZ6ztjhr0eKioC3OWrRocWnBirOjiYm1VSnOFBbfFJvWVFfj+Fu0aJGPtjhr0aLFpYUamdZcFVkz3nPWypotWlw8tMVZixYtLi0Yc+bS1fA4AwDFH1qwAyuNtjhr0eKioS3OWrRocWnBijMAGK5IcSZLBISEPWczv+esndZs0eLioC3OWrRocWkRLc5WweMM8HymVFmCuSBrrsbxt2jRIh9tcdaiRYtLCy1SnK1KzxngHXfInDnQFGklPNpatGjBh7Y4a9GixaUF8zkDVqfnDPAGGaI+Z22/WYsWFwttcdaiRYtLi1WUNQHvuOeKM7Utzlq0uEhoi7MWLVpcWqjSasqaqizBtP34JstuhwFatLhgaIuzFi1aXFpEZc1VmdYEAE2JMWftMECLFhcKbXHWokWLS4s5WXOFirN4z1nLnLVocbHQFmctWrS4tFBXdFpTjU1rtgMBLVpcLLTFWYsWLS4t5q00Vok5i/qc2W1x1qLFBUNbnLVo0eLSgmVrAqtVnGmyBCsSfN6GnrdocbHQFmctWrS4tGDGrZosoaOsDvukKpGeM6uVNVu0uGhoi7MWLVpcWhBCoMnSSrFmQILPWVuctWhxodAWZy1atLjUUGWyksWZ+f+3d/cxltV3Hcffn5m5S3cBqwIa3GVdTNBCSYEGCFisaBtFbaRpYgDbSqwENdVCU9NQTGyMMWlS09g/rIZQpIlIYwArMfbBVCq2pICldAG3KCnarlJAqTyUld3Z/frHOdO9u91ZZpO5ex7u+5Vs9p7fffpNvpk7n/t7OGdvsXdfsXt5n7s1pZExnEmaa5OlhUGdRgP2X1vzxd3LAI6cSSNjOJM01yaLCxx/zHBOowGwtBiW9+5j1+69AGz0JLTSqBjOJM214a45K15sw5nX1pTGxXAmaa6dfvLxnLn5lV1344g0a8727Q9nTmtKozKsr4uStM5uvPK8rrtwxDa0l2/atadZc+aGAGlcHDmTpIGZtCeh3T9y5vdsaUwMZ5I0MJOlg9acOXImjYrhTJIGZmXN2f7dmoYzaUwMZ5I0MBvaa4I+9397AEfOpLExnEnSwEwWm4/uZ19sw5kXPpdGxXAmSQPznXC2qwlnTmtK42I4k6SBmSztD2dLC2HDkh/l0pj4Gy1JA7Oy5uzZXXscNZNGyHAmSQMzPa3pZgBpfAxnkjQwB4YzNwNIY2M4k6SBWQlnz+3aw0Yvei6NjuFMkgZmw9LKec6WndaURshwJkkDszJy9sJLy24IkEbIcCZJA7O0sP+j25EzaXwMZ5I0MCvTmoAbAqQRMpxJ0sCsTGuCVweQxshwJkkDMx3ONrlbUxodw5kkDcwB4cyRM2l0DGeSNDAbDpjWdM2ZNDaGM0kamMkBGwIcOZPGxnAmSQPjhgBp3AxnkjQwrjmTxs1wJkkDs8FwJo2a4UySBmayuH8nvYNVAAAIIElEQVTN2caJGwKksTGcSdLALC6EtPnMkTNpfAxnkjQwSb6z7sxwJo2P4UySBmhl3Zm7NaXxMZxJ0gCtrDvzwufS+BjOJGmAnNaUxstwJkkDNFlcIIFjlvwYl8bG32pJGqDJYtg0WSTJyz9Y0qAYziRpgCaLC170XBopw5kkDdBkccH1ZtJI+bVLkgZosrTApjKcSWNkOJOkAdqwGBZiOJPGyHAmSQP0ltduYV9V192QNAOGM0kaoCvO39p1FyTNiBsCJEmSesRwJkmS1CMzC2dJbkryVJKHV7n/rUm2t//uSXJW235KkruS7EjySJJrZtVHSZKkvpnlyNnNwCWHuf9x4Cer6jXAHwA3tO3LwHuq6nTgAuCdSc6YYT8lSZJ6Y2bhrKruBp45zP33VNW32sMvAlva9ieq6oH29vPADmDzrPopSZLUJ31Zc/ZrwCcPbkyyDTgHuPco90eSJKkTnZ9KI8lP0YSziw5qPw64Hbi2qp47zPOvBq4G2LrVreWSJGnYOh05S/Ia4Ebg0qr6n6n2CU0wu6Wq7jjca1TVDVV1blWde9JJJ822w5IkSTPWWThLshW4A3h7Vf3rVHuAjwI7qupDXfVPkiSpCzOb1kxyK3AxcGKSncD7gQlAVf0Z8HvACcBHmjzGclWdC7wOeDvwUJIH25e7vqr+blZ9lSRJ6ouZhbOquuJl7r8KuOoQ7Z8HMqt+SZIk9VlfdmtKkiQJw5kkSVKvGM4kSZJ6xHAmSZLUI4YzSZKkHjGcSZIk9YjhTJIkqUdSVV33Yd0keRr4jxm/zYnAf8/4PXTkrEt/WZt+si79ZW36aRZ1+eGq+q5rT44qnB0NSf65vZKBesS69Je16Sfr0l/Wpp+OZl2c1pQkSeoRw5kkSVKPGM6O3A1dd0CHZF36y9r0k3XpL2vTT0etLq45kyRJ6hFHziRJknrEcLZGSS5J8miSx5Jc13V/5lmSU5LclWRHkkeSXNO2f3+Sv0/yb+3/39d1X+dRksUkX07yt+2xdemBJN+b5LYkX21/dy60Nt1L8u72c+zhJLcmeYV16UaSm5I8leThqbZVa5HkfW0meDTJz65nXwxna5BkEfgT4OeAM4ArkpzRba/m2jLwnqo6HbgAeGdbj+uAz1bVacBn22MdfdcAO6aOrUs/fBj4VFW9CjiLpkbWpkNJNgPvAs6tqjOBReByrEtXbgYuOajtkLVo/+ZcDry6fc5H2qywLgxna3M+8FhVfa2qdgMfBy7tuE9zq6qeqKoH2tvP0/yR2UxTk4+1D/sY8OZueji/kmwBfgG4carZunQsyfcArwc+ClBVu6vqf7E2fbAEbEyyBGwC/gvr0omquht45qDm1WpxKfDxqnqpqh4HHqPJCuvCcLY2m4FvTB3vbNvUsSTbgHOAe4EfrKonoAlwwA9017O59cfAe4F9U23WpXs/AjwN/Hk75XxjkmOxNp2qqv8E/gj4OvAE8GxVfQbr0ier1WKmucBwtjY5RJvbXDuW5DjgduDaqnqu6/7MuyRvAp6qqi913Rd9lyXgtcCfVtU5wLdxqqxz7fqlS4FTgR8Cjk3ytm57pTWaaS4wnK3NTuCUqeMtNEPP6kiSCU0wu6Wq7mibn0xycnv/ycBTXfVvTr0O+MUk/04z9f/TSf4C69IHO4GdVXVve3wbTVizNt16I/B4VT1dVXuAO4Afx7r0yWq1mGkuMJytzf3AaUlOTbKBZhHgnR33aW4lCc3amR1V9aGpu+4ErmxvXwn8zdHu2zyrqvdV1Zaq2kbzO/IPVfU2rEvnquqbwDeS/Fjb9AbgX7A2Xfs6cEGSTe3n2hto1tBal/5YrRZ3ApcnOSbJqcBpwH3r9aaehHaNkvw8zXqaReCmqvrDjrs0t5JcBPwT8BD71zZdT7Pu7K+ArTQfer9UVQcv7tRRkORi4Heq6k1JTsC6dC7J2TQbNTYAXwN+leYLurXpUJLfBy6j2YX+ZeAq4Disy1GX5FbgYuBE4Eng/cAnWKUWSX4XeAdN7a6tqk+uW18MZ5IkSf3htKYkSVKPGM4kSZJ6xHAmSZLUI4YzSZKkHjGcSZIk9YjhTNKoJLmn/X9bkl9e59e+/lDvJUnryVNpSBql6XOtHcFzFqtq72Huf6GqjluP/knSahw5kzQqSV5ob34A+IkkDyZ5d5LFJB9Mcn+S7Ul+vX38xUnuSvKXNCc2JsknknwpySNJrm7bPgBsbF/vlun3SuODSR5O8lCSy6Ze+3NJbkvy1SS3tGeCl6RVLXXdAUmakeuYGjlrQ9azVXVekmOALyT5TPvY84Ezq+rx9vgdVfVMko3A/Ulur6rrkvxWVZ19iPd6C3A2cBbN2cXvT3J3e985wKtprrv3BZprkH5+/X9cSWPhyJmkefEzwK8keZDmUl8n0FwPD+C+qWAG8K4kXwG+SHNx49M4vIuAW6tqb1U9CfwjcN7Ua++sqn3Ag8C2dflpJI2WI2eS5kWA366qTx/Q2KxN+/ZBx28ELqyqF5N8DnjFGl57NS9N3d6Ln7uSXoYjZ5LG6nng+KnjTwO/mWQCkORHkxx7iOe9EvhWG8xeBVwwdd+elecf5G7gsnZd20nA64H71uWnkDR3/AYnaay2A8vt9OTNwIdpphQfaBflPw28+RDP+xTwG0m2A4/STG2uuAHYnuSBqnrrVPtfAxcCXwEKeG9VfbMNd5J0RDyVhiRJUo84rSlJktQjhjNJkqQeMZxJkiT1iOFMkiSpRwxnkiRJPWI4kyRJ6hHDmSRJUo8YziRJknrk/wESOrCKd0fDXAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "net = init_toy_model()\n",
    "stats = net.train(X, y, X, y,\n",
    "            learning_rate=1e-1, reg=1e-5,\n",
    "            num_iters=100, verbose=False)\n",
    "\n",
    "print ('Final training loss: ', stats['loss_history'][-1])\n",
    "\n",
    "# plot the loss history\n",
    "plt.plot(stats['loss_history'])\n",
    "plt.xlabel('iteration')\n",
    "plt.ylabel('training loss')\n",
    "plt.title('Training Loss history')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the data\n",
    "Now that you have implemented a two-layer network that passes gradient checks and works on toy data, it's time to load up our favorite CIFAR-10 data so we can use it to train a classifier on a real dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  (49000, 3072)\n",
      "Train labels shape:  (49000,)\n",
      "Validation data shape:  (1000, 3072)\n",
      "Validation labels shape:  (1000,)\n",
      "Test data shape:  (1000, 3072)\n",
      "Test labels shape:  (1000,)\n"
     ]
    }
   ],
   "source": [
    "from cs231n.data_utils import load_CIFAR10\n",
    "\n",
    "def get_CIFAR10_data(num_training=49000, num_validation=1000, num_test=1000):\n",
    "    \"\"\"\n",
    "    Load the CIFAR-10 dataset from disk and perform preprocessing to prepare\n",
    "    it for the two-layer neural net classifier. These are the same steps as\n",
    "    we used for the SVM, but condensed to a single function.  \n",
    "    \"\"\"\n",
    "    # Load the raw CIFAR-10 data\n",
    "    cifar10_dir = 'cs231n/datasets/cifar-10-batches-py'\n",
    "    X_train, y_train, X_test, y_test = load_CIFAR10(cifar10_dir)\n",
    "        \n",
    "    # Subsample the data\n",
    "    mask = range(num_training, num_training + num_validation)\n",
    "    X_val = X_train[mask]\n",
    "    y_val = y_train[mask]\n",
    "    mask = range(num_training)\n",
    "    X_train = X_train[mask]\n",
    "    y_train = y_train[mask]\n",
    "    mask = range(num_test)\n",
    "    X_test = X_test[mask]\n",
    "    y_test = y_test[mask]\n",
    "\n",
    "    # Normalize the data: subtract the mean image\n",
    "    mean_image = np.mean(X_train, axis=0)\n",
    "    X_train -= mean_image\n",
    "    X_val -= mean_image\n",
    "    X_test -= mean_image\n",
    "\n",
    "    # Reshape data to rows\n",
    "    X_train = X_train.reshape(num_training, -1)\n",
    "    X_val = X_val.reshape(num_validation, -1)\n",
    "    X_test = X_test.reshape(num_test, -1)\n",
    "\n",
    "    return X_train, y_train, X_val, y_val, X_test, y_test\n",
    "\n",
    "\n",
    "# Invoke the above function to get our data.\n",
    "X_train, y_train, X_val, y_val, X_test, y_test = get_CIFAR10_data()\n",
    "print ('Train data shape: ', X_train.shape)\n",
    "print ('Train labels shape: ', y_train.shape)\n",
    "print ('Validation data shape: ', X_val.shape)\n",
    "print ('Validation labels shape: ', y_val.shape)\n",
    "print ('Test data shape: ', X_test.shape)\n",
    "print ('Test labels shape: ', y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train a network\n",
    "To train our network we will use SGD with momentum. In addition, we will adjust the learning rate with an exponential learning rate schedule as optimization proceeds; after each epoch, we will reduce the learning rate by multiplying it by a decay rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1000: loss 2.302970\n",
      "iteration 100 / 1000: loss 2.302474\n",
      "iteration 200 / 1000: loss 2.297076\n",
      "iteration 300 / 1000: loss 2.257325\n",
      "iteration 400 / 1000: loss 2.230484\n",
      "iteration 500 / 1000: loss 2.150618\n",
      "iteration 600 / 1000: loss 2.080737\n",
      "iteration 700 / 1000: loss 2.054923\n",
      "iteration 800 / 1000: loss 1.979293\n",
      "iteration 900 / 1000: loss 2.039101\n",
      "Validation accuracy:  0.287\n"
     ]
    }
   ],
   "source": [
    "input_size = 32 * 32 * 3\n",
    "hidden_size = 50\n",
    "num_classes = 10\n",
    "net = TwoLayerNet(input_size, hidden_size, num_classes)\n",
    "\n",
    "# Train the network\n",
    "stats = net.train(X_train, y_train, X_val, y_val,\n",
    "            num_iters=1000, batch_size=200,\n",
    "            learning_rate=1e-4, learning_rate_decay=0.95,\n",
    "            reg=0.5, verbose=True)\n",
    "\n",
    "# Predict on the validation set\n",
    "val_acc = (net.predict(X_val) == y_val).mean()\n",
    "print ('Validation accuracy: ', val_acc)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Debug the training\n",
    "With the default parameters we provided above, you should get a validation accuracy of about 0.29 on the validation set. This isn't very good.\n",
    "\n",
    "One strategy for getting insight into what's wrong is to plot the loss function and the accuracies on the training and validation sets during optimization.\n",
    "\n",
    "Another strategy is to visualize the weights that were learned in the first layer of the network. In most neural networks trained on visual data, the first layer weights typically show some visible structure when visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the loss function and train / validation accuracies\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(stats['loss_history'])\n",
    "plt.title('Loss history')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Loss')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.plot(stats['train_acc_history'], label='train')\n",
    "plt.plot(stats['val_acc_history'], label='val')\n",
    "plt.title('Classification accuracy history')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Clasification accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from cs231n.vis_utils import visualize_grid\n",
    "\n",
    "# Visualize the weights of the network\n",
    "\n",
    "def show_net_weights(net):\n",
    "  W1 = net.params['W1']\n",
    "  W1 = W1.reshape(32, 32, 3, -1).transpose(3, 0, 1, 2)\n",
    "  plt.imshow(visualize_grid(W1, padding=3).astype('uint8'))\n",
    "  plt.gca().axis('off')\n",
    "  plt.show()\n",
    "\n",
    "show_net_weights(net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tune your hyperparameters\n",
    "\n",
    "**What's wrong?**. Looking at the visualizations above, we see that the loss is decreasing more or less linearly, which seems to suggest that the learning rate may be too low. Moreover, there is no gap between the training and validation accuracy, suggesting that the model we used has low capacity, and that we should increase its size. On the other hand, with a very large model we would expect to see more overfitting, which would manifest itself as a very large gap between the training and validation accuracy.\n",
    "\n",
    "**Tuning**. Tuning the hyperparameters and developing intuition for how they affect the final performance is a large part of using Neural Networks, so we want you to get a lot of practice. Below, you should experiment with different values of the various hyperparameters, including hidden layer size, learning rate, numer of training epochs, and regularization strength. You might also consider tuning the learning rate decay, but you should be able to get good performance using the default value.\n",
    "\n",
    "**Approximate results**. You should be aim to achieve a classification accuracy of greater than 48% on the validation set. Our best network gets over 52% on the validation set.\n",
    "\n",
    "**Experiment**: You goal in this exercise is to get as good of a result on CIFAR-10 as you can, with a fully-connected Neural Network. For every 1% above 52% on the Test set we will award you with one extra bonus point. Feel free implement your own techniques (e.g. PCA to reduce dimensionality, or adding dropout, or adding features to the solver, etc.)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "iteration 700 / 1000: loss 1.766709\n",
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      "iteration 900 / 1000: loss 1.586158\n",
      "lr 1.000000e-03 ld 9.000000e-01  reg 3.000000e+00 bs 3.000000e+02 hidder_size:2.000000e+02\n",
      "iteration 0 / 1000: loss 2.311785\n",
      "iteration 100 / 1000: loss 1.947998\n",
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      "iteration 700 / 1000: loss 1.700596\n",
      "iteration 800 / 1000: loss 1.738693\n",
      "iteration 900 / 1000: loss 1.774587\n",
      "lr 1.000000e-03 ld 9.000000e-01  reg 3.000000e+00 bs 4.000000e+02 hidder_size:5.000000e+01\n",
      "iteration 0 / 1000: loss 2.304883\n",
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      "iteration 700 / 1000: loss 1.631847\n",
      "iteration 800 / 1000: loss 1.721596\n",
      "iteration 900 / 1000: loss 1.739138\n",
      "lr 1.000000e-03 ld 9.000000e-01  reg 3.000000e+00 bs 4.000000e+02 hidder_size:1.000000e+02\n",
      "iteration 0 / 1000: loss 2.307182\n",
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      "iteration 700 / 1000: loss 1.756047\n",
      "iteration 800 / 1000: loss 1.727218\n",
      "iteration 900 / 1000: loss 1.728364\n",
      "lr 1.000000e-03 ld 9.000000e-01  reg 3.000000e+00 bs 4.000000e+02 hidder_size:1.500000e+02\n",
      "iteration 0 / 1000: loss 2.309530\n",
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      "iteration 700 / 1000: loss 1.769641\n",
      "iteration 800 / 1000: loss 1.708265\n",
      "iteration 900 / 1000: loss 1.746342\n",
      "lr 1.000000e-03 ld 9.000000e-01  reg 3.000000e+00 bs 4.000000e+02 hidder_size:2.000000e+02\n",
      "iteration 0 / 1000: loss 2.311797\n",
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      "iteration 700 / 1000: loss 1.699949\n",
      "iteration 800 / 1000: loss 1.741798\n",
      "iteration 900 / 1000: loss 1.627271\n",
      "lr 1.000000e-03 ld 9.500000e-01  reg 1.000000e+00 bs 2.000000e+02 hidder_size:5.000000e+01\n",
      "iteration 0 / 1000: loss 2.303381\n",
      "iteration 100 / 1000: loss 1.938198\n",
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      "iteration 700 / 1000: loss 1.632857\n",
      "iteration 800 / 1000: loss 1.755265\n",
      "iteration 900 / 1000: loss 1.617162\n",
      "lr 1.000000e-03 ld 9.500000e-01  reg 1.000000e+00 bs 2.000000e+02 hidder_size:1.000000e+02\n",
      "iteration 0 / 1000: loss 2.304157\n",
      "iteration 100 / 1000: loss 1.923600\n",
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      "iteration 300 / 1000: loss 1.685268\n",
      "iteration 400 / 1000: loss 1.543459\n",
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      "iteration 600 / 1000: loss 1.562454\n",
      "iteration 700 / 1000: loss 1.567581\n",
      "iteration 800 / 1000: loss 1.539528\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 900 / 1000: loss 1.506201\n",
      "lr 1.000000e-03 ld 9.500000e-01  reg 1.000000e+00 bs 2.000000e+02 hidder_size:1.500000e+02\n",
      "iteration 0 / 1000: loss 2.304909\n",
      "iteration 100 / 1000: loss 1.967266\n",
      "iteration 200 / 1000: loss 1.753916\n",
      "iteration 300 / 1000: loss 1.722816\n",
      "iteration 400 / 1000: loss 1.683845\n",
      "iteration 500 / 1000: loss 1.650992\n",
      "iteration 600 / 1000: loss 1.461059\n",
      "iteration 700 / 1000: loss 1.558350\n",
      "iteration 800 / 1000: loss 1.478760\n",
      "iteration 900 / 1000: loss 1.489101\n",
      "lr 1.000000e-03 ld 9.500000e-01  reg 1.000000e+00 bs 2.000000e+02 hidder_size:2.000000e+02\n",
      "iteration 0 / 1000: loss 2.305628\n",
      "iteration 100 / 1000: loss 1.943715\n",
      "iteration 200 / 1000: loss 1.729596\n",
      "iteration 300 / 1000: loss 1.624107\n",
      "iteration 400 / 1000: loss 1.558537\n",
      "iteration 500 / 1000: loss 1.614544\n",
      "iteration 600 / 1000: loss 1.510040\n",
      "iteration 700 / 1000: loss 1.570618\n",
      "iteration 800 / 1000: loss 1.549364\n",
      "iteration 900 / 1000: loss 1.615733\n",
      "lr 1.000000e-03 ld 9.500000e-01  reg 1.000000e+00 bs 3.000000e+02 hidder_size:5.000000e+01\n",
      "iteration 0 / 1000: loss 2.303362\n",
      "iteration 100 / 1000: loss 1.943033\n",
      "iteration 200 / 1000: loss 1.825125\n",
      "iteration 300 / 1000: loss 1.766346\n",
      "iteration 400 / 1000: loss 1.632059\n",
      "iteration 500 / 1000: loss 1.548045\n",
      "iteration 600 / 1000: loss 1.580245\n",
      "iteration 700 / 1000: loss 1.633941\n",
      "iteration 800 / 1000: loss 1.570440\n",
      "iteration 900 / 1000: loss 1.530921\n",
      "lr 1.000000e-03 ld 9.500000e-01  reg 1.000000e+00 bs 3.000000e+02 hidder_size:1.000000e+02\n",
      "iteration 0 / 1000: loss 2.304133\n",
      "iteration 100 / 1000: loss 1.941985\n",
      "iteration 200 / 1000: loss 1.830264\n",
      "iteration 300 / 1000: loss 1.707777\n",
      "iteration 400 / 1000: loss 1.603317\n",
      "iteration 500 / 1000: loss 1.527195\n",
      "iteration 600 / 1000: loss 1.587148\n",
      "iteration 700 / 1000: loss 1.466039\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-20-cb42e2a1c8d0>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     27\u001b[0m                     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'lr %e ld %e  reg %e bs %e hidder_size:%e'\u001b[0m\u001b[1;33m%\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mld\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrg\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mbs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mhidden_size\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     28\u001b[0m                     \u001b[0mnet\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTwoLayerNet\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhidden_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnum_classes\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 29\u001b[1;33m                     net.train(X_train,y_train,X_val,y_val,learning_rate=lr,learning_rate_decay=ld,\n\u001b[0m\u001b[0;32m     30\u001b[0m                           num_iters=1000,batch_size=bs,reg=rg,verbose=True)\n\u001b[0;32m     31\u001b[0m                     \u001b[0mYValPred\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnet\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_val\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mG:\\cs231n_code\\assignment1\\cs231n\\classifiers\\neural_net.py\u001b[0m in \u001b[0;36mtrain\u001b[1;34m(self, X, y, X_val, y_val, learning_rate, learning_rate_decay, reg, num_iters, batch_size, verbose)\u001b[0m\n\u001b[0;32m    171\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    172\u001b[0m       \u001b[1;31m# Compute loss and gradients using the current minibatch\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 173\u001b[1;33m       \u001b[0mloss\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgrads\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloss\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_batch\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my_batch\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mreg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    174\u001b[0m       \u001b[0mloss_history\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;31m# 记录历史loss\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mG:\\cs231n_code\\assignment1\\cs231n\\classifiers\\neural_net.py\u001b[0m in \u001b[0;36mloss\u001b[1;34m(self, X, y, reg)\u001b[0m\n\u001b[0;32m    119\u001b[0m     \u001b[0mdhidden\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mhidden_scores\u001b[0m\u001b[1;33m<=\u001b[0m\u001b[1;36m0.00001\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    120\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 121\u001b[1;33m     \u001b[0mgrads\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'W1'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mdhidden\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mreg\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mW1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    122\u001b[0m     \u001b[0mgrads\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'b1'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdhidden\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    123\u001b[0m     \u001b[1;31m#############################################################################\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mdot\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "best_net = None # store the best model into this \n",
    "best_accuracy=-1\n",
    "batchSizes=[200,300,400]\n",
    "learningRates=[1e-3,5e-4,1e-4,5e-5]\n",
    "learningDecays=[0.8,0.85,0.9,0.95]\n",
    "regs=[1,2.5,3]\n",
    "hiddenSizes=[50,100,150,200]\n",
    "results={}\n",
    "#################################################################################\n",
    "# TODO: Tune hyperparameters using the validation set. Store your best trained  #\n",
    "# model in best_net.                                                            #\n",
    "#                                                                               #\n",
    "# To help debug your network, it may help to use visualizations similar to the  #\n",
    "# ones we used above; these visualizations will have significant qualitative    #\n",
    "# differences from the ones we saw above for the poorly tuned network.          #\n",
    "#                                                                               #\n",
    "# Tweaking hyperparameters by hand can be fun, but you might find it useful to  #\n",
    "# write code to sweep through possible combinations of hyperparameters          #\n",
    "# automatically like we did on the previous exercises.                          #\n",
    "#################################################################################\n",
    "pass\n",
    "for lr in learningRates:\n",
    "    for ld in learningDecays:\n",
    "        for rg in regs:\n",
    "            for bs in batchSizes:\n",
    "                for hidden_size in hiddenSizes:\n",
    "                    print('lr %e ld %e  reg %e bs %e hidder_size:%e'%(lr,ld,rg,bs,hidden_size))\n",
    "                    net = TwoLayerNet(input_size, hidden_size, num_classes)\n",
    "                    net.train(X_train,y_train,X_val,y_val,learning_rate=lr,learning_rate_decay=ld,\n",
    "                          num_iters=1000,batch_size=bs,reg=rg,verbose=True)\n",
    "                    YValPred=net.predict(X_val)\n",
    "                    Val_accuracy=(YValPred==y_val).mean()\n",
    "                    YTrainPred=net.predict(X_train)\n",
    "                    Train_accuracy=(YTrainPred==y_train).mean()\n",
    "                    results[(lr,ld,rg,bs,hidden_size)]=(Train_accuracy,Val_accuracy)\n",
    "                    if Val_accuracy>best_accuracy:\n",
    "                        best_accuracy=Val_accuracy\n",
    "                        best_net=net\n",
    "#################################################################################\n",
    "#                               END OF YOUR CODE                                #\n",
    "#################################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# visualize the weights of the best network\n",
    "for lr,ld,reg,bs,hs in sorted(results):\n",
    "    train_accuracy, val_accuracy = results[(lr,ld, reg,bs,hs)]\n",
    "    print('lr %e ld %e  reg %e bs %e hidden_Size:%e train accuracy: %f val accuracy: %f' % (\n",
    "                lr,ld, reg,bs, hs,train_accuracy, val_accuracy))\n",
    "    if val_accuracy==best_accuracy:\n",
    "        best_parameter=(lr,ld,reg,bs,hs)\n",
    "print('best_parameter:lr:%f,ld:%f,reg:%f,bs:%f,hs:%f'%(best_parameter[0],best_parameter[1],best_parameter[2],best_parameter[3],best_parameter[4]))\n",
    "print('best_accuracy: %f' % (best_accuracy))\n",
    "val_acc = (best_net.predict(X_val) == y_val).mean()\n",
    "print('Validation accuracy: ', val_acc)\n",
    "show_net_weights(best_net)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run on the test set\n",
    "When you are done experimenting, you should evaluate your final trained network on the test set; you should get above 48%.\n",
    "\n",
    "**We will give you extra bonus point for every 1% of accuracy above 52%.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_acc = (best_net.predict(X_test) == y_test).mean()\n",
    "print ('Test accuracy: ', test_acc)\n",
    "import pickle\n",
    "pickle.dump(results,open('results.pkl','wb'))\n",
    "pickle.dump(best_accuracy,open('best_accuracy.pkl','wb'))\n",
    "pickle.dump(best_net.params,open('best_net.pkl','wb'))"
   ]
  }
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